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   "source": [
    "#!/usr/bin/python3\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "\n",
    "stock_day_change=np.load('./stock_day_change.npy')\n",
    "stock_day_change.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "22e21042",
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       "      <td>0.954369</td>\n",
       "      <td>-0.334769</td>\n",
       "      <td>-0.922828</td>\n",
       "      <td>-0.365397</td>\n",
       "      <td>-1.333122</td>\n",
       "      <td>0.555532</td>\n",
       "      <td>-0.642221</td>\n",
       "      <td>-1.545224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>股票1</th>\n",
       "      <td>0.342909</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.298828</td>\n",
       "      <td>-1.501727</td>\n",
       "      <td>0.042856</td>\n",
       "      <td>0.810229</td>\n",
       "      <td>0.700401</td>\n",
       "      <td>-0.174594</td>\n",
       "      <td>1.003943</td>\n",
       "      <td>...</td>\n",
       "      <td>1.243326</td>\n",
       "      <td>1.311459</td>\n",
       "      <td>0.720127</td>\n",
       "      <td>1.093422</td>\n",
       "      <td>0.035059</td>\n",
       "      <td>1.965103</td>\n",
       "      <td>0.160549</td>\n",
       "      <td>-0.664439</td>\n",
       "      <td>-0.097399</td>\n",
       "      <td>0.598844</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 504 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          0    1         2         3         4         5         6    \\\n",
       "股票0  1.000000  1.0 -0.403738 -0.550034  1.000000 -1.138161 -1.184134   \n",
       "股票1  0.342909  1.0  1.000000 -0.298828 -1.501727  0.042856  0.810229   \n",
       "\n",
       "          7         8         9    ...       494       495       496  \\\n",
       "股票0  0.281419  1.076455  1.324160  ... -0.258830  1.116188  0.954369   \n",
       "股票1  0.700401 -0.174594  1.003943  ...  1.243326  1.311459  0.720127   \n",
       "\n",
       "          497       498       499       500       501       502       503  \n",
       "股票0 -0.334769 -0.922828 -0.365397 -1.333122  0.555532 -0.642221 -1.545224  \n",
       "股票1  1.093422  0.035059  1.965103  0.160549 -0.664439 -0.097399  0.598844  \n",
       "\n",
       "[2 rows x 504 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 股票 0-> 股票 stock_day_change.shape(0)\n",
    "stock_symbols=['股票'+str(x) for  x in range(stock_day_change.shape[0])]\n",
    "#print(stock_symbols)\n",
    "pd.DataFrame(stock_day_change,index=stock_symbols).head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7dfbd5ac",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2018-01-01</th>\n",
       "      <th>2018-01-02</th>\n",
       "      <th>2018-01-03</th>\n",
       "      <th>2018-01-04</th>\n",
       "      <th>2018-01-05</th>\n",
       "      <th>2018-01-06</th>\n",
       "      <th>2018-01-07</th>\n",
       "      <th>2018-01-08</th>\n",
       "      <th>2018-01-09</th>\n",
       "      <th>2018-01-10</th>\n",
       "      <th>...</th>\n",
       "      <th>2019-05-10</th>\n",
       "      <th>2019-05-11</th>\n",
       "      <th>2019-05-12</th>\n",
       "      <th>2019-05-13</th>\n",
       "      <th>2019-05-14</th>\n",
       "      <th>2019-05-15</th>\n",
       "      <th>2019-05-16</th>\n",
       "      <th>2019-05-17</th>\n",
       "      <th>2019-05-18</th>\n",
       "      <th>2019-05-19</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>股票0</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.403738</td>\n",
       "      <td>-0.550034</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-1.138161</td>\n",
       "      <td>-1.184134</td>\n",
       "      <td>0.281419</td>\n",
       "      <td>1.076455</td>\n",
       "      <td>1.324160</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.258830</td>\n",
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       "      <td>-1.333122</td>\n",
       "      <td>0.555532</td>\n",
       "      <td>-0.642221</td>\n",
       "      <td>-1.545224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>股票1</th>\n",
       "      <td>0.342909</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.298828</td>\n",
       "      <td>-1.501727</td>\n",
       "      <td>0.042856</td>\n",
       "      <td>0.810229</td>\n",
       "      <td>0.700401</td>\n",
       "      <td>-0.174594</td>\n",
       "      <td>1.003943</td>\n",
       "      <td>...</td>\n",
       "      <td>1.243326</td>\n",
       "      <td>1.311459</td>\n",
       "      <td>0.720127</td>\n",
       "      <td>1.093422</td>\n",
       "      <td>0.035059</td>\n",
       "      <td>1.965103</td>\n",
       "      <td>0.160549</td>\n",
       "      <td>-0.664439</td>\n",
       "      <td>-0.097399</td>\n",
       "      <td>0.598844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>股票2</th>\n",
       "      <td>-0.479775</td>\n",
       "      <td>-0.326376</td>\n",
       "      <td>0.067287</td>\n",
       "      <td>0.414201</td>\n",
       "      <td>1.533611</td>\n",
       "      <td>-0.527330</td>\n",
       "      <td>0.877844</td>\n",
       "      <td>0.817033</td>\n",
       "      <td>-0.959725</td>\n",
       "      <td>0.588928</td>\n",
       "      <td>...</td>\n",
       "      <td>0.856078</td>\n",
       "      <td>0.377186</td>\n",
       "      <td>-1.361635</td>\n",
       "      <td>-0.357984</td>\n",
       "      <td>0.310347</td>\n",
       "      <td>1.585126</td>\n",
       "      <td>0.718140</td>\n",
       "      <td>-0.212988</td>\n",
       "      <td>-1.638737</td>\n",
       "      <td>-2.058938</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>股票3</th>\n",
       "      <td>-0.412637</td>\n",
       "      <td>-0.057664</td>\n",
       "      <td>-0.191728</td>\n",
       "      <td>-0.953936</td>\n",
       "      <td>0.719906</td>\n",
       "      <td>-2.045009</td>\n",
       "      <td>0.421210</td>\n",
       "      <td>-1.578283</td>\n",
       "      <td>1.560339</td>\n",
       "      <td>0.240931</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.695341</td>\n",
       "      <td>-1.019046</td>\n",
       "      <td>0.078635</td>\n",
       "      <td>1.121134</td>\n",
       "      <td>0.207282</td>\n",
       "      <td>1.097827</td>\n",
       "      <td>-1.403285</td>\n",
       "      <td>-0.229031</td>\n",
       "      <td>0.763190</td>\n",
       "      <td>-1.533688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>股票4</th>\n",
       "      <td>-0.197876</td>\n",
       "      <td>-1.212699</td>\n",
       "      <td>1.663287</td>\n",
       "      <td>-0.322057</td>\n",
       "      <td>-0.891702</td>\n",
       "      <td>1.299376</td>\n",
       "      <td>-0.809181</td>\n",
       "      <td>-0.300684</td>\n",
       "      <td>-0.748764</td>\n",
       "      <td>-1.475458</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.327731</td>\n",
       "      <td>-0.266038</td>\n",
       "      <td>0.375683</td>\n",
       "      <td>0.108972</td>\n",
       "      <td>-0.151249</td>\n",
       "      <td>-0.001873</td>\n",
       "      <td>-0.255218</td>\n",
       "      <td>-0.677437</td>\n",
       "      <td>1.512976</td>\n",
       "      <td>0.449192</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 504 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     2018-01-01  2018-01-02  2018-01-03  2018-01-04  2018-01-05  2018-01-06  \\\n",
       "股票0    1.000000    1.000000   -0.403738   -0.550034    1.000000   -1.138161   \n",
       "股票1    0.342909    1.000000    1.000000   -0.298828   -1.501727    0.042856   \n",
       "股票2   -0.479775   -0.326376    0.067287    0.414201    1.533611   -0.527330   \n",
       "股票3   -0.412637   -0.057664   -0.191728   -0.953936    0.719906   -2.045009   \n",
       "股票4   -0.197876   -1.212699    1.663287   -0.322057   -0.891702    1.299376   \n",
       "\n",
       "     2018-01-07  2018-01-08  2018-01-09  2018-01-10  ...  2019-05-10  \\\n",
       "股票0   -1.184134    0.281419    1.076455    1.324160  ...   -0.258830   \n",
       "股票1    0.810229    0.700401   -0.174594    1.003943  ...    1.243326   \n",
       "股票2    0.877844    0.817033   -0.959725    0.588928  ...    0.856078   \n",
       "股票3    0.421210   -1.578283    1.560339    0.240931  ...   -0.695341   \n",
       "股票4   -0.809181   -0.300684   -0.748764   -1.475458  ...   -1.327731   \n",
       "\n",
       "     2019-05-11  2019-05-12  2019-05-13  2019-05-14  2019-05-15  2019-05-16  \\\n",
       "股票0    1.116188    0.954369   -0.334769   -0.922828   -0.365397   -1.333122   \n",
       "股票1    1.311459    0.720127    1.093422    0.035059    1.965103    0.160549   \n",
       "股票2    0.377186   -1.361635   -0.357984    0.310347    1.585126    0.718140   \n",
       "股票3   -1.019046    0.078635    1.121134    0.207282    1.097827   -1.403285   \n",
       "股票4   -0.266038    0.375683    0.108972   -0.151249   -0.001873   -0.255218   \n",
       "\n",
       "     2019-05-17  2019-05-18  2019-05-19  \n",
       "股票0    0.555532   -0.642221   -1.545224  \n",
       "股票1   -0.664439   -0.097399    0.598844  \n",
       "股票2   -0.212988   -1.638737   -2.058938  \n",
       "股票3   -0.229031    0.763190   -1.533688  \n",
       "股票4   -0.677437    1.512976    0.449192  \n",
       "\n",
       "[5 rows x 504 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "days=pd.date_range('2018-1-1', periods=stock_day_change.shape[1], freq='1d')\n",
    "df=pd.DataFrame(stock_day_change,index=stock_symbols, columns=days)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "cfc770d6",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>股票0</th>\n",
       "      <th>股票1</th>\n",
       "      <th>股票2</th>\n",
       "      <th>股票3</th>\n",
       "      <th>股票4</th>\n",
       "      <th>股票5</th>\n",
       "      <th>股票6</th>\n",
       "      <th>股票7</th>\n",
       "      <th>股票8</th>\n",
       "      <th>股票9</th>\n",
       "      <th>...</th>\n",
       "      <th>股票190</th>\n",
       "      <th>股票191</th>\n",
       "      <th>股票192</th>\n",
       "      <th>股票193</th>\n",
       "      <th>股票194</th>\n",
       "      <th>股票195</th>\n",
       "      <th>股票196</th>\n",
       "      <th>股票197</th>\n",
       "      <th>股票198</th>\n",
       "      <th>股票199</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-01-01</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.342909</td>\n",
       "      <td>-0.479775</td>\n",
       "      <td>-0.412637</td>\n",
       "      <td>-0.197876</td>\n",
       "      <td>-0.477118</td>\n",
       "      <td>1.122262</td>\n",
       "      <td>1.165408</td>\n",
       "      <td>0.706623</td>\n",
       "      <td>1.313030</td>\n",
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       "      <td>0.533153</td>\n",
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       "      <td>-0.086517</td>\n",
       "      <td>1.569378</td>\n",
       "      <td>1.257341</td>\n",
       "      <td>0.166168</td>\n",
       "      <td>-1.093842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-02</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.326376</td>\n",
       "      <td>-0.057664</td>\n",
       "      <td>-1.212699</td>\n",
       "      <td>-0.049191</td>\n",
       "      <td>-0.873814</td>\n",
       "      <td>0.601161</td>\n",
       "      <td>1.132342</td>\n",
       "      <td>-0.280508</td>\n",
       "      <td>...</td>\n",
       "      <td>1.367459</td>\n",
       "      <td>0.262058</td>\n",
       "      <td>-0.117142</td>\n",
       "      <td>1.178611</td>\n",
       "      <td>-0.984449</td>\n",
       "      <td>0.322695</td>\n",
       "      <td>0.590053</td>\n",
       "      <td>-0.464075</td>\n",
       "      <td>0.236278</td>\n",
       "      <td>-0.988803</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 200 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            股票0       股票1       股票2       股票3       股票4       股票5       股票6  \\\n",
       "2018-01-01  1.0  0.342909 -0.479775 -0.412637 -0.197876 -0.477118  1.122262   \n",
       "2018-01-02  1.0  1.000000 -0.326376 -0.057664 -1.212699 -0.049191 -0.873814   \n",
       "\n",
       "                 股票7       股票8       股票9  ...     股票190     股票191     股票192  \\\n",
       "2018-01-01  1.165408  0.706623  1.313030  ...  1.336485  0.533153 -0.638464   \n",
       "2018-01-02  0.601161  1.132342 -0.280508  ...  1.367459  0.262058 -0.117142   \n",
       "\n",
       "               股票193     股票194     股票195     股票196     股票197     股票198  \\\n",
       "2018-01-01 -0.036262  1.481692 -0.086517  1.569378  1.257341  0.166168   \n",
       "2018-01-02  1.178611 -0.984449  0.322695  0.590053 -0.464075  0.236278   \n",
       "\n",
       "               股票199  \n",
       "2018-01-01 -1.093842  \n",
       "2018-01-02 -0.988803  \n",
       "\n",
       "[2 rows x 200 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#df=df.transpose()\n",
    "df=df.T\n",
    "df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "28520093",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>股票0</th>\n",
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       "      <th>股票2</th>\n",
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       "      <th>股票191</th>\n",
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       "      <th>股票196</th>\n",
       "      <th>股票197</th>\n",
       "      <th>股票198</th>\n",
       "      <th>股票199</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-01-01</th>\n",
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       "      <td>-0.199150</td>\n",
       "      <td>0.348535</td>\n",
       "      <td>0.507168</td>\n",
       "      <td>0.274294</td>\n",
       "      <td>-0.065795</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.067803</td>\n",
       "      <td>0.127094</td>\n",
       "      <td>0.106274</td>\n",
       "      <td>0.014081</td>\n",
       "      <td>-0.401131</td>\n",
       "      <td>0.288893</td>\n",
       "      <td>0.134077</td>\n",
       "      <td>-0.507609</td>\n",
       "      <td>-0.078247</td>\n",
       "      <td>-0.110567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-22</th>\n",
       "      <td>-0.396628</td>\n",
       "      <td>-0.140550</td>\n",
       "      <td>-0.049854</td>\n",
       "      <td>-0.067959</td>\n",
       "      <td>-0.328661</td>\n",
       "      <td>-0.008739</td>\n",
       "      <td>-0.293583</td>\n",
       "      <td>-0.035746</td>\n",
       "      <td>-0.118276</td>\n",
       "      <td>-0.104932</td>\n",
       "      <td>...</td>\n",
       "      <td>0.084755</td>\n",
       "      <td>-0.124349</td>\n",
       "      <td>0.081615</td>\n",
       "      <td>-0.122209</td>\n",
       "      <td>0.012597</td>\n",
       "      <td>-0.145379</td>\n",
       "      <td>-0.002780</td>\n",
       "      <td>-0.085212</td>\n",
       "      <td>0.094785</td>\n",
       "      <td>-0.093843</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-12</th>\n",
       "      <td>-0.144847</td>\n",
       "      <td>-0.288831</td>\n",
       "      <td>-0.135292</td>\n",
       "      <td>-0.221860</td>\n",
       "      <td>-0.101344</td>\n",
       "      <td>-0.450415</td>\n",
       "      <td>0.143861</td>\n",
       "      <td>-0.059293</td>\n",
       "      <td>-0.363434</td>\n",
       "      <td>-0.378559</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.106247</td>\n",
       "      <td>0.200407</td>\n",
       "      <td>-0.022609</td>\n",
       "      <td>0.000907</td>\n",
       "      <td>-0.323432</td>\n",
       "      <td>-0.156902</td>\n",
       "      <td>0.019207</td>\n",
       "      <td>0.007825</td>\n",
       "      <td>0.003895</td>\n",
       "      <td>0.432720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-05</th>\n",
       "      <td>-0.049795</td>\n",
       "      <td>-0.283583</td>\n",
       "      <td>0.100277</td>\n",
       "      <td>-0.195060</td>\n",
       "      <td>-0.062274</td>\n",
       "      <td>-0.154678</td>\n",
       "      <td>-0.069592</td>\n",
       "      <td>0.022966</td>\n",
       "      <td>-0.177476</td>\n",
       "      <td>-0.016546</td>\n",
       "      <td>...</td>\n",
       "      <td>0.008450</td>\n",
       "      <td>-0.138882</td>\n",
       "      <td>0.361727</td>\n",
       "      <td>-0.156759</td>\n",
       "      <td>0.208556</td>\n",
       "      <td>0.087038</td>\n",
       "      <td>0.027950</td>\n",
       "      <td>-0.059063</td>\n",
       "      <td>-0.126070</td>\n",
       "      <td>0.408253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-26</th>\n",
       "      <td>-0.060109</td>\n",
       "      <td>-0.057964</td>\n",
       "      <td>-0.302418</td>\n",
       "      <td>0.331237</td>\n",
       "      <td>0.162384</td>\n",
       "      <td>0.379788</td>\n",
       "      <td>0.197323</td>\n",
       "      <td>0.197116</td>\n",
       "      <td>0.082111</td>\n",
       "      <td>0.167401</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.364602</td>\n",
       "      <td>-0.099766</td>\n",
       "      <td>-0.146484</td>\n",
       "      <td>0.235883</td>\n",
       "      <td>-0.307911</td>\n",
       "      <td>0.114590</td>\n",
       "      <td>0.091912</td>\n",
       "      <td>0.195757</td>\n",
       "      <td>0.209262</td>\n",
       "      <td>-0.065533</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 200 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 股票0       股票1       股票2       股票3       股票4       股票5  \\\n",
       "2018-01-01  0.014227  0.114313 -0.140332 -0.046919 -0.488106 -0.199150   \n",
       "2018-01-22 -0.396628 -0.140550 -0.049854 -0.067959 -0.328661 -0.008739   \n",
       "2018-02-12 -0.144847 -0.288831 -0.135292 -0.221860 -0.101344 -0.450415   \n",
       "2018-03-05 -0.049795 -0.283583  0.100277 -0.195060 -0.062274 -0.154678   \n",
       "2018-03-26 -0.060109 -0.057964 -0.302418  0.331237  0.162384  0.379788   \n",
       "\n",
       "                 股票6       股票7       股票8       股票9  ...     股票190     股票191  \\\n",
       "2018-01-01  0.348535  0.507168  0.274294 -0.065795  ... -0.067803  0.127094   \n",
       "2018-01-22 -0.293583 -0.035746 -0.118276 -0.104932  ...  0.084755 -0.124349   \n",
       "2018-02-12  0.143861 -0.059293 -0.363434 -0.378559  ... -0.106247  0.200407   \n",
       "2018-03-05 -0.069592  0.022966 -0.177476 -0.016546  ...  0.008450 -0.138882   \n",
       "2018-03-26  0.197323  0.197116  0.082111  0.167401  ... -0.364602 -0.099766   \n",
       "\n",
       "               股票192     股票193     股票194     股票195     股票196     股票197  \\\n",
       "2018-01-01  0.106274  0.014081 -0.401131  0.288893  0.134077 -0.507609   \n",
       "2018-01-22  0.081615 -0.122209  0.012597 -0.145379 -0.002780 -0.085212   \n",
       "2018-02-12 -0.022609  0.000907 -0.323432 -0.156902  0.019207  0.007825   \n",
       "2018-03-05  0.361727 -0.156759  0.208556  0.087038  0.027950 -0.059063   \n",
       "2018-03-26 -0.146484  0.235883 -0.307911  0.114590  0.091912  0.195757   \n",
       "\n",
       "               股票198     股票199  \n",
       "2018-01-01 -0.078247 -0.110567  \n",
       "2018-01-22  0.094785 -0.093843  \n",
       "2018-02-12  0.003895  0.432720  \n",
       "2018-03-05 -0.126070  0.408253  \n",
       "2018-03-26  0.209262 -0.065533  \n",
       "\n",
       "[5 rows x 200 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#df.head()\n",
    "#在resample()函数中how已经不再使用了,改成  .median()\n",
    "df_20=df.resample('21D').mean()\n",
    "df_20.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ffd179a1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.series.Series'>\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "2018-01-01    1.000000\n",
       "2018-01-02    1.000000\n",
       "2018-01-03   -0.403738\n",
       "2018-01-04   -0.550034\n",
       "2018-01-05    1.000000\n",
       "Freq: D, Name: 股票0, dtype: float64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_stock0=df['股票0']\n",
    "print(type(df_stock0))\n",
    "df_stock0.head()\n",
    "#Series是pandas中一个非常中亚的累，可以简单地理解Series是只有一列数据的DataFrame对象。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "0d92aa23",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#本质上pandas在给予封装Numpy的数据操作上海风撞了Matplotlib\n",
    "df_stock0.cumsum().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "4dddc32e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-01-01</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.917585</td>\n",
       "      <td>-0.276066</td>\n",
       "      <td>0.298767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-22</th>\n",
       "      <td>0.260393</td>\n",
       "      <td>0.260393</td>\n",
       "      <td>-8.030417</td>\n",
       "      <td>-8.030417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-12</th>\n",
       "      <td>-8.845159</td>\n",
       "      <td>-6.295125</td>\n",
       "      <td>-12.159147</td>\n",
       "      <td>-11.072214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-05</th>\n",
       "      <td>-9.056206</td>\n",
       "      <td>-6.723027</td>\n",
       "      <td>-12.117911</td>\n",
       "      <td>-12.117911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-26</th>\n",
       "      <td>-13.170470</td>\n",
       "      <td>-9.656052</td>\n",
       "      <td>-15.091551</td>\n",
       "      <td>-13.380201</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 open      high        low      close\n",
       "2018-01-01   1.000000  4.917585  -0.276066   0.298767\n",
       "2018-01-22   0.260393  0.260393  -8.030417  -8.030417\n",
       "2018-02-12  -8.845159 -6.295125 -12.159147 -11.072214\n",
       "2018-03-05  -9.056206 -6.723027 -12.117911 -12.117911\n",
       "2018-03-26 -13.170470 -9.656052 -15.091551 -13.380201"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_stock0_5=df_stock0.cumsum().resample('5D').ohlc()\n",
    "df_stock0_5=df_stock0.cumsum().resample('21D').ohlc()\n",
    "df_stock0_5.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "b3b55340",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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XwXJXy/GxY8e0du1a3X333VqxYoVatGhR7LF79uxRbGysKlSoYEXpgN+1zsdOp1ORkZGqWLGisrKy5HK5rCwbuKyrrYePHTumJUuW6O6779ayZcu0evVq7dy5U7169ZIkHTlyRFlZWYqNjbVyCICkwm+s1qxZU4899pg6d+6scuXKacWKFZIKD/xd2HipUaOGnn76aa1atcp2B0wQuo4eParMzEzdfvvtkgo/1zVt2lQ9evTQ559/rk8++USSVKpUKUmFN3Lu1KmTGjZsqJkzZ1pVNsLQ1bK6c+dOf1a9Xq+ysrLk9Xr9jz1+/LgiIyNVvnx5K0oH/K6U4wcffFDbt2/Xli1b1Lt3b23YsKHYlWUk6cCBA7Y8xkbTBaapW7eucnNztXfvXknyH6R+4IEHVLduXW3fvl3JycmSVOwfiWHDhmnv3r22vH4fgteV8tq1a1d/Xk+cOKHMzEzNmTNH8+fPV0ZGhlJTU/V///d/uvfee1WtWjUrhwBcNce33367tmzZ4r9vwIYNG7Rw4UJlZWUpLS1NH3/8sRo3buy/KSNglWuZj4vWD5J03333ac+ePUpNTbWkXuBqfmle3rZtm44ePSrDMHTs2DG9//778ng8SktL03/+8x898sgjXLoUAXO1K40nJCRozJgxqly5su644w794Q9/0NGjR/Xee+9d8liHw6H27durevXq2rx5c4nXDVyLBg0aKDs7W19//bUkqaCgQJLUv39/xcbG6rPPPtPp06cl/ff4RHx8vJ555hlt3bqVLCNgriWrqamp+vnnnzVr1iytW7dObrdbZ86c0d69e9W5c2eaLrDc1XIcFxenzZs369SpU5Kk999/X++//77cbrfS0tK0fft2tWjRQpUqVbKs/pLAih6/2uUW50WLlIceekhLly6VVHiqeUFBgWJjY9WmTRtlZmbqq6++kqRiHyZvueUWjRkzRvfff38Aqke4uZG87tmzR2XKlJHP59P8+fP15JNPqnv37vr555/19NNP+69lDZS0683xuXPntG/fPhUUFGjPnj2aPn26+vfvr27duik5OVnDhw8vdlovUJLMWD9IhWfJRkVF6a9//WtgCgcu40bm5aKGzKFDhzR69GgNHDhQDzzwgHJyctS+ffvADQJh6aefftKuXbuUmprqv7nthV+IkwrzHR0drfLly/sPmnTu3Fk1atTQe++9p7Nnz8owjGKPu+mmm7RixQo9//zzgRsMcBWGYahjx47629/+Jum/83GFChXUpUsX7du3z//lpAuPTyQmJur555/3f1sbKGm/lNW9e/fq+PHjqlChgo4dO6ZRo0ZpwIAB6t69u9LS0tSnTx+LRwBc25x78uRJ5ebm6r333tNLL72kp556St26ddPPP/+sZ555xnZfPLLXaFBifmlxXvTG6NSpkzwej/903KIPpB06dJDX69Xx48clyf87ivTu3dt/czDgRpmV1x9++EGlSpXSyJEj9cEHH2jYsGGaOnWqVq1apRo1agR2UAg7ZuTY4/HoyJEjcjqdevnll7Vu3ToNHjxYU6ZM0erVq1WzZs3ADgphp6TWDyNHjlT37t0DNQxAknnz8o8//ihJevjhh7V48WJ169ZNEyZM0NKlS5WQkBDAESGceDwejR49Wj169NAbb7yhXr16acmSJZL+m92iBovD4fDntujeAdWrV1e7du2Unp6u1atX+/e7UHx8fEDGAqSkpMjlciknJ8e/7eLmYenSpdW2bVudO3fO3wgv2uexxx7TuXPn9MMPP1zy2JiYGA0ePJjPezCFGVnNysrSN998o5iYGM2YMUOrV6/Wo48+qkmTJmnlypWqWrVq4AaEsGTWnPvdd98pOjpaU6ZM0ZIlS9S1a1dNmDBBq1atUvXq1QM3oABxWl0AgpvH49HYsWP10UcfqWrVqsrKytJjjz2mp556qtjivGgxXqtWLQ0YMECzZ89W165dVadOHfl8PjkcDlWuXNl/eRBufIuSYHZeiw7yORwO1alTR3Xq1LFsbAgfJZXjmJgYNWjQQA0aNLBsbAgfJb1+6NSpkzUDQ1gqqTxHRkaqcePGaty4sWVjQ/hYuXKl9u3bp7///e+Ki4vTvHnztHHjRt1///2qXbu2fD6fP8NLlizRiRMn9Mwzzyg+Pt6f3/bt22v37t1699131bp1a9WrV8/iUSHcFBQUaOzYsdqyZYuqV68ut9utxx9/XD169LjsfPy73/1O999/vxYtWqRu3bqpfPny8ng8ioiI0G9+8xv/fGy3b1fDemZn9eTJk5Kk2NhYNWrUSI0aNbJsbAgfZuf4xIkTkgovYZqQkKDmzZtbNrZA4F8WXNWFi/M5c+aoefPm2rhxo/8behcvzmfPnq17771XTZs21Ysvvqjvv/9eDodDp06dksvlUpcuXawcDmzO7Lw+8MADVg4HYYocww5YP8BOmJcR6txut9atW6dWrVqpQYMGqlGjhpo1aybDMFSrVi1JhV8y+vzzz9WxY0f9/e9/V/Pmzf1nrhSd+RIbG6v7779fd999t8qVK2fhiBCu5s2bp2+++UZvvvmmRo4cqcaNG2vatGlatWqVpOIH/xYvXqyPPvpIbdu2VXx8vF544QVlZmYqIiJCx48fV3p6Opc4R4khq7ADs3Pcpk0bK4cTcJzpgisqWpy3bt3a/83oZs2a6dChQ5cszkePHq2cnBy99tprql+/vmbMmKEBAwZowIABuv3223Xw4EHdcsst+t3vfmfhiGBn5BV2QI5hB+QYdkKeEYqysrIUExMjwzDk8XhUqlQpVapUSV9//bXy8/N1+vRprVq1Sj6fT7Nnz1azZs3UqFEjLVmyRJ06ddJTTz2l2NjYYr+z6FJibdq0CbuDJggOGRkZWr9+vR5++GHdeeedkqRq1aopLy9PU6ZM0X333afKlStrx44dGj9+vDIyMvTGG2/o7rvv1uTJkzVw4ED17NlTDRs21J49e1S/fn3Vq1fPfyYXYBayCjsgxzeOpgv8zFqcezwexcfHa968eTpw4ID27dunbt26qWvXrlYPETZCXmEH5Bh2QI5hJ+QZoe7IkSMaP368evbsqQceeEARERHy+Xxq27atJk2apJ49e+rw4cNq1aqVbr31Vu3cuVMLFy7U/PnzNXXqVJUpU8bqIQCSis/HkpSWlqZSpUqpYsWK/n3i4+PVsGFDrVu3TosWLdLTTz+tyZMnq0OHDhowYIBiY2Pl8/lUt25dvf3229q3b5++/fZbvfDCC+rRo4dFI4PdkFXYATk2n8NXdIc8hLWLF+dS4aUS3n33XU2aNElVq1Yttjj/6quv9M0332j+/Plq0qQJi3MEFHmFHZBj2AE5hp2QZ4Qyr9crwzC0fft2JSUlqVOnTnrllVf8lwhzu906duyYZs2apapVq+qll15SqVKllJubq5EjR2r//v36xz/+YfEogEKXm4/z8/PVoUMHtWzZUi+88ILKly8vSVq1apXee+897d27V1u2bFGVKlW4RwsChqzCDshxyeBZCXNer1eSdOrUKe3atUtbt25VWlqapMJTyLt3764VK1aoZs2a6tu3r+bMmaNhw4Zp8eLF6tixo8aPH88HTAQMeYUdkGPYATmGnZBn2EHRAY8vvvhChmHo6NGj+vjjj/0/L1WqlG677TbFxcWpfv36KlWqlCQpOjpaTzzxhFwulw4dOmRJ7UCRq83HpUqV0qBBg7RlyxZNnDhRBw8e1PLly7VgwQL169dPTZs21fz58zn4h4Agq7ADclyyeGbCHItzhBLyCjsgx7ADcgw7Ic8IRRdfsMLr9erw4cPatGmThg0bpooVK2rLli06cuSIf5/U1FQdPHhQZ8+elcfj8W//7rvvVKFCBZUtWzZg9QOX80vz8aOPPqonn3xS+/fv16BBgzRnzhwNHz5cXbp0Ua1atZSfn18s20BJIauwA3Jcsmi6hBkW5wgl5BV2QI5hB+QYdkKeEermz5+vcePGadGiRTp16pSkwgMnqampatiwofr166dHHnlELpdLGzdulFR41tZNN92km2++WR988IH+9a9/KTc3V2fOnNGuXbvUunVrVatWzcphIQxdz3w8YMAArVu3TsuXL9fOnTvVuXNnSZLL5VJGRoYiIiICOgaEB7IKOyDHgUXTJYywOEcoIa+wA3IMOyDHsBPyjFDmcrnUs2dPbdq0SQ6HQ3/961/1wgsvaPPmzZKk2rVr6/XXX5fD4VC7du3UoEED7dy5U7t27fL/jlGjRqlixYr685//rKSkJHXr1k3p6ekaPHiwVcNCmLqe+VgqPEgYGRmp1NRU7dixQ5J08uRJnTt3Tg8//LAlY4G9kVXYATkOPIfv4jYXbMflcmnIkCHKz89X8+bN9eGHH6pOnTrq37+/2rdvL5fLpcjISFWoUEGS9NJLLyk5OVnPP/+8mjdvLklKSUnRiBEjtGvXLjVp0kQ//PCD6tatq4kTJ6py5cpWDg82Q15hB+QYdkCOYSfkGXbw4YcfasWKFXrrrbcUHx+vH3/8UfPmzdO2bdv0ySef+M+4crvdioyM1L59+zRq1Cg1btxYr7zyiqKioiRJaWlpOnz4sFwulypXruzPOBAIZszH58+f16xZs7Ru3Tr9/ve/11dffaW77rpLEydO5MxDmIaswg7IsXVouoQBFucIJeQVdkCOYQfkGHZCnhGK8vLylJ6ertjYWJUpU0YTJ07Uzp079f777/v3+eGHH/Tss8/qjjvu0NSpU+Xz+eRwOPw/nz59urZt26akpCR17tz5kp8DgWbmfPzNN9/o0KFDqlu3rlq1amXlsGBDZBV2QI6tw+XFbCgvL08ul0vZ2dmSpP379+v8+fOKj4+XVHjaeVJSksqVK6cxY8ZIKryuX2RkpCSpUaNG+sMf/qC9e/fq008/9f88Pj5ezZs3V7du3fiACdOQV9gBOYYdkGPYCXlGqFu4cKE6duyoP/3pT+rdu7e2b9+uiIgIxcfH6/jx4/796tSpoz/96U/auHGjvv32WzkcDnk8Hnm9XklSnz59VKZMGa1du1Yul4uGCwKuJOfjVq1aKSkpiYN/MAVZhR2Q4+BB08VmWJwjlJBX2AE5hh2QY9gJeUYo83g8mjBhgjZu3KiXX35ZQ4cOVUJCgubPny+Xy6VTp07pwIED/v0dDodatmypxMREzZw5U5IUEREhwzDk9XpVuXJltWvXTtWqVfN/WxUIFOZjhAqyCjsgx8GFpotNsDhHKCGvsANyDDsgx7AT8gw7OHv2rD7//HP169dPHTp00L333qvp06frxIkTaty4sZxOpzZs2CCXy+V/TNmyZdW1a1cdO3ZMP/74o3970UGS/v37a/z48Spfvnygh4MwxXyMUEFWYQfkODjRdLEJFucIJeQVdkCOYQfkGHZCnmEHycnJOnTokJo0aSJJ8nq9qlChgsqWLav09HSNHz9eW7du1b///W/l5eVJkpxOpxISEuT1elWqVCn/7+KbqbAK8zFCBVmFHZDj4ETTxSZYnCOUkFfYATmGHZBj2Al5hh3Ur19fbdu2ldvtliQZhqHU1FSlpKQoOjpajRo1Urt27bRmzRpt27bN/7iMjAyVLl1aMTExVpUO+DEfI1SQVdgBOQ5ONF1sgsU5Qgl5hR2QY9gBOYadkGfYQenSpfXGG2/olltu8W/78ccflZ2drYYNG0qSXnvtNVWpUkXjx4/XmDFjtGjRIk2bNk1t27blG6kICszHCBVkFXZAjoOT0+oCYI6ixfmFb5TLLc7HjBmj8ePHa8eOHapWrZqWLl2qnj17sjhHQJFX2AE5hh2QY9gJeYZdxMXFFfvztm3bVLVqVbVo0UIej0cJCQkaP368NmzYoF27dmnfvn3+m+YCwYD5GKGCrMIOyHFwcvh8Pp/VRaBkTJ8+XR9//LE++eQTeTweRUREKCMjw784d7lc6tWrF4tzBAXyCjsgx7ADcgw7Ic8Idenp6XrooYd0zz336C9/+YskKS0tTZ9++qm6devGDW4RMpiPESrIKuyAHFuPM11sKj09XZs2bdI999wjSYqIiPAvzv/4xz/qiSeesLhC4L/IK+yAHMMOyDHshDzDDr7//nv99NNP6tGjhyRp/vz5mj17tjp06KAuXbrI5/Nx/XUEPeZjhAqyCjsgx8GBe7rY1OUW5y1bttSOHTvk8XjECU4IJuQVdkCOYQfkGHZCnmEHhw8fVtWqVbV//3516NBBa9as0dy5czVjxgzFxMTQcEFIYD5GqCCrsANyHBw408WmLlycjxgxQvn5+Zo7d65at25tdWnAJcgr7IAcww7IMeyEPMMOcnJy9NNPP2nmzJkaPHiwkpKSrC4J+NWYjxEqyCrsgBwHB5ouNsXiHKGEvMIOyDHsgBzDTsgz7KB27doaOnSoBg4cqMjISKvLAa4L8zFCBVmFHZDj4ODwcU6RLX366ac6dOgQi3OEBPIKOyDHsANyDDshz7AD7tkCO2A+Rqggq7ADchwcaLrYFItzhBLyCjsgx7ADcgw7Ic8AEByYjxEqyCrsgBwHB5ouAAAAAAAAAAAAJjCsLgAAAAAAAAAAAMAOaLoAAAAAAAAAAACYgKYLAAAAAAAAAACACWi6AAAAAAAAAAAAmICmCwAAAAAAAAAAgAlougAAAAAAAAAAAJiApgsAAAAAAAAAAIAJaLoAAAAAAAAAAACYgKYLAAAAAAAAAACACWi6AAAAAAAAAAAAmOD/AWyKdBTaKqY/AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 2000x1200 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'numpy.ndarray'>\n",
      "DatetimeIndex(['2018-01-01', '2018-01-22', '2018-02-12', '2018-03-05',\n",
      "               '2018-03-26', '2018-04-16', '2018-05-07', '2018-05-28',\n",
      "               '2018-06-18', '2018-07-09', '2018-07-30', '2018-08-20',\n",
      "               '2018-09-10', '2018-10-01', '2018-10-22', '2018-11-12',\n",
      "               '2018-12-03', '2018-12-24', '2019-01-14', '2019-02-04',\n",
      "               '2019-02-25', '2019-03-18', '2019-04-08', '2019-04-29'],\n",
      "              dtype='datetime64[ns]', freq='21D')\n",
      "Index(['open', 'high', 'low', 'close'], dtype='object')\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import sys\n",
    "# 使用insert 0即只使用github，避免交叉使用了pip安装的abupy，导致的版本不一致问题\n",
    "#print(os.path.abspath('../'))\n",
    "sys.path.insert(0, os.path.abspath('../canna'))\n",
    "from canna import ABuMarketDrawing\n",
    "import canna\n",
    "canna.__version__\n",
    "\"\"\"\n",
    "WARNING: `mpl_finance` is deprecated:\n",
    "\n",
    "    Please use `mplfinance` instead (no hyphen, no underscore).\n",
    "\n",
    "    To install: `pip install --upgrade mplfinance` \n",
    "\"\"\"\n",
    "ABuMarketDrawing.plot_candle_stick(df_stock0_5.index,\n",
    "                                   df_stock0_5['open'].values,\n",
    "                                   df_stock0_5['high'].values,\n",
    "                                   df_stock0_5['low'].values,\n",
    "                                   df_stock0_5['close'].values,\n",
    "                                   np.random.random(len(df_stock0_5)),\n",
    "                                                    None,'stock',day_sum=False,\n",
    "                                                    html_bk=False, save=False)\n",
    "print(type(df_stock0_5['open'].values))\n",
    "print(df_stock0_5['open'].index)\n",
    "print(df_stock0_5.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "7be264d9",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.series.Series'>\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>change</th>\n",
       "      <th>pct_chg</th>\n",
       "      <th>vol</th>\n",
       "      <th>amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20210707</td>\n",
       "      <td>62.690000</td>\n",
       "      <td>63.410000</td>\n",
       "      <td>62.090000</td>\n",
       "      <td>62.370000</td>\n",
       "      <td>62.900000</td>\n",
       "      <td>-0.530000</td>\n",
       "      <td>-0.842600</td>\n",
       "      <td>523167.540000</td>\n",
       "      <td>3272128.188000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20210706</td>\n",
       "      <td>62.420000</td>\n",
       "      <td>63.140000</td>\n",
       "      <td>61.850000</td>\n",
       "      <td>62.900000</td>\n",
       "      <td>61.910000</td>\n",
       "      <td>0.990000</td>\n",
       "      <td>1.599100</td>\n",
       "      <td>685812.850000</td>\n",
       "      <td>4296674.949000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20210705</td>\n",
       "      <td>61.990000</td>\n",
       "      <td>62.280000</td>\n",
       "      <td>61.130000</td>\n",
       "      <td>61.910000</td>\n",
       "      <td>62.300000</td>\n",
       "      <td>-0.390000</td>\n",
       "      <td>-0.626000</td>\n",
       "      <td>750646.750000</td>\n",
       "      <td>4629283.875000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20210702</td>\n",
       "      <td>64.030000</td>\n",
       "      <td>64.070000</td>\n",
       "      <td>62.100000</td>\n",
       "      <td>62.300000</td>\n",
       "      <td>64.760000</td>\n",
       "      <td>-2.460000</td>\n",
       "      <td>-3.798600</td>\n",
       "      <td>1028081.620000</td>\n",
       "      <td>6464701.802000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20210701</td>\n",
       "      <td>64.260000</td>\n",
       "      <td>65.170000</td>\n",
       "      <td>63.580000</td>\n",
       "      <td>64.760000</td>\n",
       "      <td>64.280000</td>\n",
       "      <td>0.480000</td>\n",
       "      <td>0.746700</td>\n",
       "      <td>692617.350000</td>\n",
       "      <td>4449223.158000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       ts_code trade_date      open      high       low     close  pre_close  \\\n",
       "156  601318.SH   20210707 62.690000 63.410000 62.090000 62.370000  62.900000   \n",
       "157  601318.SH   20210706 62.420000 63.140000 61.850000 62.900000  61.910000   \n",
       "158  601318.SH   20210705 61.990000 62.280000 61.130000 61.910000  62.300000   \n",
       "159  601318.SH   20210702 64.030000 64.070000 62.100000 62.300000  64.760000   \n",
       "160  601318.SH   20210701 64.260000 65.170000 63.580000 64.760000  64.280000   \n",
       "\n",
       "       change   pct_chg            vol         amount  \n",
       "156 -0.530000 -0.842600  523167.540000 3272128.188000  \n",
       "157  0.990000  1.599100  685812.850000 4296674.949000  \n",
       "158 -0.390000 -0.626000  750646.750000 4629283.875000  \n",
       "159 -2.460000 -3.798600 1028081.620000 6464701.802000  \n",
       "160  0.480000  0.746700  692617.350000 4449223.158000  "
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#from canna import ABuSymbolPd\n",
    "#tsla_df=ABuSymbolPd.make_kl_df('usTSLA',n_folds=2)\n",
    "#import pandas.io.data as web\n",
    "import tushare as ts\n",
    "import json\n",
    "\n",
    "def obj_to_Json(obj):\n",
    "    data = json.dumps(obj, indent=4,ensure_ascii=False)\n",
    "    fh = open('data.json', 'w')\n",
    "    fh.write(data)\n",
    "    fh.close()  # 最终写入的json文件格式:\n",
    "\n",
    "#print(ts.__version__)\n",
    "#ts.set_token('dfeb543866c1b2b3e804f3cbed560e9e1709b0d06cd8182e1cc5676d')\n",
    "pro = ts.pro_api('ea3263c5424f08c3e04d605af9458cfc349613d5b7c27e99994eb396')\n",
    "#ts_pro.get_hist_data('601318') \n",
    "start='20210701'\n",
    "end='20220301'\n",
    "# 中国平安 代替 Tesla at p78\n",
    "zgpa_df = pro.daily(ts_code='601318.SH', start_date=start, end_date=end)\n",
    "#print(zgpa_df.head())\n",
    "#print(type(zgpa_df))\n",
    "import matplotlib.pyplot as plt\n",
    "print(type(zgpa_df['trade_date']))\n",
    "zgpa_df[['close','vol']].plot(subplots=True, style=['r','g'],grid=True)\n",
    "zgpa_df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "7edf666d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<Axes: xlabel='trade_date'>, <Axes: xlabel='trade_date'>],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#print(zgpa_df['trade_date'].tolist())\n",
    "x=zgpa_df['trade_date'].tolist()\n",
    "zgpa_df[['trade_date','close','vol']].plot(x='trade_date',subplots=True, style=['r','g'],grid=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "586f523f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     ts_code trade_date      open      high       low     close  pre_close  \\\n",
      "4  601318.SH   20220223 53.100000 53.300000 52.690000 52.890000  53.070000   \n",
      "3  601318.SH   20220224 52.150000 52.250000 51.090000 51.460000  52.890000   \n",
      "2  601318.SH   20220225 51.700000 52.060000 51.210000 51.400000  51.460000   \n",
      "1  601318.SH   20220228 51.100000 51.100000 50.250000 50.760000  51.400000   \n",
      "0  601318.SH   20220301 51.010000 51.400000 50.570000 51.390000  50.760000   \n",
      "\n",
      "     change   pct_chg           vol         amount  \n",
      "4 -0.180000 -0.339200 463601.660000 2449763.789000  \n",
      "3 -1.430000 -2.703700 975396.020000 5039207.433000  \n",
      "2 -0.060000 -0.116600 544416.390000 2808109.116000  \n",
      "1 -0.640000 -1.245100 731883.260000 3707888.597000  \n",
      "0  0.630000  1.241100 568035.790000 2895181.121000  \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>change</th>\n",
       "      <th>pct_chg</th>\n",
       "      <th>vol</th>\n",
       "      <th>amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>161.000000</td>\n",
       "      <td>161.000000</td>\n",
       "      <td>161.000000</td>\n",
       "      <td>161.000000</td>\n",
       "      <td>161.000000</td>\n",
       "      <td>161.000000</td>\n",
       "      <td>161.000000</td>\n",
       "      <td>161.000000</td>\n",
       "      <td>161.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>52.441615</td>\n",
       "      <td>53.059130</td>\n",
       "      <td>51.855652</td>\n",
       "      <td>52.432547</td>\n",
       "      <td>52.507205</td>\n",
       "      <td>-0.074658</td>\n",
       "      <td>-0.113016</td>\n",
       "      <td>736850.077888</td>\n",
       "      <td>3875538.775155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.353605</td>\n",
       "      <td>3.373038</td>\n",
       "      <td>3.190242</td>\n",
       "      <td>3.271509</td>\n",
       "      <td>3.398848</td>\n",
       "      <td>0.947885</td>\n",
       "      <td>1.793644</td>\n",
       "      <td>311928.909872</td>\n",
       "      <td>1671132.876016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>47.500000</td>\n",
       "      <td>48.080000</td>\n",
       "      <td>47.300000</td>\n",
       "      <td>47.780000</td>\n",
       "      <td>47.780000</td>\n",
       "      <td>-3.140000</td>\n",
       "      <td>-5.447600</td>\n",
       "      <td>274701.060000</td>\n",
       "      <td>1373481.524000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>50.290000</td>\n",
       "      <td>50.940000</td>\n",
       "      <td>49.810000</td>\n",
       "      <td>50.280000</td>\n",
       "      <td>50.280000</td>\n",
       "      <td>-0.560000</td>\n",
       "      <td>-1.127000</td>\n",
       "      <td>523167.540000</td>\n",
       "      <td>2723626.777000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>51.500000</td>\n",
       "      <td>52.150000</td>\n",
       "      <td>51.060000</td>\n",
       "      <td>51.490000</td>\n",
       "      <td>51.550000</td>\n",
       "      <td>-0.150000</td>\n",
       "      <td>-0.295000</td>\n",
       "      <td>669800.000000</td>\n",
       "      <td>3558132.760000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>53.500000</td>\n",
       "      <td>54.180000</td>\n",
       "      <td>52.880000</td>\n",
       "      <td>53.650000</td>\n",
       "      <td>53.650000</td>\n",
       "      <td>0.440000</td>\n",
       "      <td>0.788700</td>\n",
       "      <td>880434.530000</td>\n",
       "      <td>4629283.875000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>64.260000</td>\n",
       "      <td>65.170000</td>\n",
       "      <td>63.580000</td>\n",
       "      <td>64.760000</td>\n",
       "      <td>64.760000</td>\n",
       "      <td>3.740000</td>\n",
       "      <td>7.733700</td>\n",
       "      <td>2180028.230000</td>\n",
       "      <td>11318517.616000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            open       high        low      close  pre_close     change  \\\n",
       "count 161.000000 161.000000 161.000000 161.000000 161.000000 161.000000   \n",
       "mean   52.441615  53.059130  51.855652  52.432547  52.507205  -0.074658   \n",
       "std     3.353605   3.373038   3.190242   3.271509   3.398848   0.947885   \n",
       "min    47.500000  48.080000  47.300000  47.780000  47.780000  -3.140000   \n",
       "25%    50.290000  50.940000  49.810000  50.280000  50.280000  -0.560000   \n",
       "50%    51.500000  52.150000  51.060000  51.490000  51.550000  -0.150000   \n",
       "75%    53.500000  54.180000  52.880000  53.650000  53.650000   0.440000   \n",
       "max    64.260000  65.170000  63.580000  64.760000  64.760000   3.740000   \n",
       "\n",
       "         pct_chg            vol          amount  \n",
       "count 161.000000     161.000000      161.000000  \n",
       "mean   -0.113016  736850.077888  3875538.775155  \n",
       "std     1.793644  311928.909872  1671132.876016  \n",
       "min    -5.447600  274701.060000  1373481.524000  \n",
       "25%    -1.127000  523167.540000  2723626.777000  \n",
       "50%    -0.295000  669800.000000  3558132.760000  \n",
       "75%     0.788700  880434.530000  4629283.875000  \n",
       "max     7.733700 2180028.230000 11318517.616000  "
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x700 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pandas.plotting import register_matplotlib_converters\n",
    "register_matplotlib_converters()\n",
    "# 对中国平安数据进行逆序\n",
    "zgpa_df = zgpa_df.sort_index(axis=0, ascending=False)\n",
    "print(zgpa_df.tail())\n",
    "# x='trade_date', 将trade_date列作为X轴标签\n",
    "zgpa_df[['trade_date','open','close','vol']].plot(x='trade_date',subplots=True, \n",
    "                                           style=['r','b','g'],grid=True, xlabel='Date')\n",
    "zgpa_df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "2a72b010",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<Axes: xlabel='Date'>, <Axes: xlabel='Date'>,\n",
       "       <Axes: xlabel='Date'>], dtype=object)"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x700 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "#font = FontProperties(fname='/System/Library/Fonts/Supplemental/Songti.ttf')\n",
    "pd.set_option('float_format', '{:f}'.format)\n",
    "zgpa_df[['trade_date','open','close','vol']].plot(x='trade_date',subplots=True, \n",
    "                                           style=['r','b','g'],grid=True, xlabel='Date', title=zgpa_df['ts_code'][0])\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "af4e00e0",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "\n",
    "#plt.style.use('ggplot')\n",
    "plt.plot(zgpa_df['trade_date'], zgpa_df['open'], \"g\")\n",
    "plt.grid(axis=\"y\")\n",
    "#plt.plot(ma.index, ma, \"b\");\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "6efec2fa",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       ts_code trade_date      open      high       low     close  pre_close  \\\n",
      "160  601318.SH   20210701 64.260000 65.170000 63.580000 64.760000  64.280000   \n",
      "159  601318.SH   20210702 64.030000 64.070000 62.100000 62.300000  64.760000   \n",
      "158  601318.SH   20210705 61.990000 62.280000 61.130000 61.910000  62.300000   \n",
      "157  601318.SH   20210706 62.420000 63.140000 61.850000 62.900000  61.910000   \n",
      "156  601318.SH   20210707 62.690000 63.410000 62.090000 62.370000  62.900000   \n",
      "\n",
      "       change   pct_chg            vol         amount  \n",
      "160  0.480000  0.746700  692617.350000 4449223.158000  \n",
      "159 -2.460000 -3.798600 1028081.620000 6464701.802000  \n",
      "158 -0.390000 -0.626000  750646.750000 4629283.875000  \n",
      "157  0.990000  1.599100  685812.850000 4296674.949000  \n",
      "156 -0.530000 -0.842600  523167.540000 3272128.188000  \n"
     ]
    },
    {
     "data": {
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>64.030000</td>\n",
       "      <td>64.070000</td>\n",
       "      <td>62.100000</td>\n",
       "      <td>62.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>61.990000</td>\n",
       "      <td>62.280000</td>\n",
       "      <td>61.130000</td>\n",
       "      <td>61.910000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>62.420000</td>\n",
       "      <td>63.140000</td>\n",
       "      <td>61.850000</td>\n",
       "      <td>62.900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>62.690000</td>\n",
       "      <td>63.410000</td>\n",
       "      <td>62.090000</td>\n",
       "      <td>62.370000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         open      high       low     close\n",
       "159 64.030000 64.070000 62.100000 62.300000\n",
       "158 61.990000 62.280000 61.130000 61.910000\n",
       "157 62.420000 63.140000 61.850000 62.900000\n",
       "156 62.690000 63.410000 62.090000 62.370000"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(zgpa_df.head())\n",
    "zgpa_df.iloc[1:5,2:6]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "4211de95",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "160   64.760000\n",
      "159   62.300000\n",
      "158   61.910000\n",
      "Name: close, dtype: float64\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>64.760000</td>\n",
       "      <td>65.170000</td>\n",
       "      <td>63.580000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>62.300000</td>\n",
       "      <td>64.070000</td>\n",
       "      <td>62.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>61.910000</td>\n",
       "      <td>62.280000</td>\n",
       "      <td>61.130000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        close      high       low\n",
       "160 64.760000 65.170000 63.580000\n",
       "159 62.300000 64.070000 62.100000\n",
       "158 61.910000 62.280000 61.130000"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(zgpa_df.close[0:3])\n",
    "zgpa_df[['close','high','low']][0:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "ef4c5f48",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       ts_code trade_date      open      high       low     close  pre_close  \\\n",
      "143  601318.SH   20210726 57.090000 57.090000 54.330000 54.500000  57.640000   \n",
      "96   601318.SH   20211008 50.500000 52.100000 50.110000 52.100000  48.360000   \n",
      "87   601318.SH   20211021 51.550000 54.880000 51.510000 54.280000  51.370000   \n",
      "\n",
      "       change   pct_chg            vol          amount  netChangeRatio  \n",
      "143 -3.140000 -5.447600 1174864.670000  6496203.840000       -0.054476  \n",
      "96   3.740000  7.733700 2180028.230000 11199501.310000        0.077337  \n",
      "87   2.910000  5.664800 2110058.330000 11318517.616000        0.056648  \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "ts_code                601318.SH\n",
       "trade_date              20211008\n",
       "open                   50.500000\n",
       "high                   52.100000\n",
       "low                    50.110000\n",
       "close                  52.100000\n",
       "pre_close              48.360000\n",
       "change                  3.740000\n",
       "pct_chg                 7.733700\n",
       "vol               2180028.230000\n",
       "amount           11199501.310000\n",
       "netChangeRatio          0.077337\n",
       "Name: 96, dtype: object"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# pct_chg is netChangeRatio，命名差异而已\n",
    "zgpa_df['netChangeRatio']=np.true_divide(zgpa_df['change'], zgpa_df['pre_close'])\n",
    "\n",
    "print(zgpa_df[np.abs(zgpa_df['netChangeRatio'])>0.05])\n",
    "n=np.abs(zgpa_df['netChangeRatio'][zgpa_df['netChangeRatio']!=0]).argmax()\n",
    "zgpa_df.iloc[n]\n",
    "#np.abs(zgpa_df['netChangeRatio'][zgpa_df['netChangeRatio']!=0]).max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "6635fa42",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>change</th>\n",
       "      <th>pct_chg</th>\n",
       "      <th>vol</th>\n",
       "      <th>amount</th>\n",
       "      <th>netChangeRatio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20211008</td>\n",
       "      <td>50.500000</td>\n",
       "      <td>52.100000</td>\n",
       "      <td>50.110000</td>\n",
       "      <td>52.100000</td>\n",
       "      <td>48.360000</td>\n",
       "      <td>3.740000</td>\n",
       "      <td>7.733700</td>\n",
       "      <td>2180028.230000</td>\n",
       "      <td>11199501.310000</td>\n",
       "      <td>0.077337</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20211021</td>\n",
       "      <td>51.550000</td>\n",
       "      <td>54.880000</td>\n",
       "      <td>51.510000</td>\n",
       "      <td>54.280000</td>\n",
       "      <td>51.370000</td>\n",
       "      <td>2.910000</td>\n",
       "      <td>5.664800</td>\n",
       "      <td>2110058.330000</td>\n",
       "      <td>11318517.616000</td>\n",
       "      <td>0.056648</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      ts_code trade_date      open      high       low     close  pre_close  \\\n",
       "96  601318.SH   20211008 50.500000 52.100000 50.110000 52.100000  48.360000   \n",
       "87  601318.SH   20211021 51.550000 54.880000 51.510000 54.280000  51.370000   \n",
       "\n",
       "     change  pct_chg            vol          amount  netChangeRatio  \n",
       "96 3.740000 7.733700 2180028.230000 11199501.310000        0.077337  \n",
       "87 2.910000 5.664800 2110058.330000 11318517.616000        0.056648  "
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zgpa_df[np.abs(zgpa_df['netChangeRatio']>0.02)&(zgpa_df.vol>2.5*zgpa_df.vol.mean())]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "dcafc098",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>change</th>\n",
       "      <th>pct_chg</th>\n",
       "      <th>vol</th>\n",
       "      <th>amount</th>\n",
       "      <th>netChangeRatio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20210927</td>\n",
       "      <td>47.900000</td>\n",
       "      <td>49.240000</td>\n",
       "      <td>47.820000</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>48.080000</td>\n",
       "      <td>0.920000</td>\n",
       "      <td>1.913500</td>\n",
       "      <td>990080.990000</td>\n",
       "      <td>4812486.506000</td>\n",
       "      <td>0.019135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20210928</td>\n",
       "      <td>48.990000</td>\n",
       "      <td>49.630000</td>\n",
       "      <td>48.520000</td>\n",
       "      <td>49.260000</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>0.260000</td>\n",
       "      <td>0.530600</td>\n",
       "      <td>779506.960000</td>\n",
       "      <td>3832059.452000</td>\n",
       "      <td>0.005306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20210929</td>\n",
       "      <td>48.770000</td>\n",
       "      <td>49.540000</td>\n",
       "      <td>48.520000</td>\n",
       "      <td>49.190000</td>\n",
       "      <td>49.260000</td>\n",
       "      <td>-0.070000</td>\n",
       "      <td>-0.142100</td>\n",
       "      <td>631295.330000</td>\n",
       "      <td>3095105.433000</td>\n",
       "      <td>-0.001421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20210930</td>\n",
       "      <td>49.300000</td>\n",
       "      <td>49.300000</td>\n",
       "      <td>48.230000</td>\n",
       "      <td>48.360000</td>\n",
       "      <td>49.190000</td>\n",
       "      <td>-0.830000</td>\n",
       "      <td>-1.687300</td>\n",
       "      <td>680070.250000</td>\n",
       "      <td>3300543.923000</td>\n",
       "      <td>-0.016873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20211008</td>\n",
       "      <td>50.500000</td>\n",
       "      <td>52.100000</td>\n",
       "      <td>50.110000</td>\n",
       "      <td>52.100000</td>\n",
       "      <td>48.360000</td>\n",
       "      <td>3.740000</td>\n",
       "      <td>7.733700</td>\n",
       "      <td>2180028.230000</td>\n",
       "      <td>11199501.310000</td>\n",
       "      <td>0.077337</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20211011</td>\n",
       "      <td>52.100000</td>\n",
       "      <td>53.390000</td>\n",
       "      <td>51.940000</td>\n",
       "      <td>52.740000</td>\n",
       "      <td>52.100000</td>\n",
       "      <td>0.640000</td>\n",
       "      <td>1.228400</td>\n",
       "      <td>1504499.540000</td>\n",
       "      <td>7944560.509000</td>\n",
       "      <td>0.012284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20211012</td>\n",
       "      <td>52.050000</td>\n",
       "      <td>53.040000</td>\n",
       "      <td>51.680000</td>\n",
       "      <td>52.260000</td>\n",
       "      <td>52.740000</td>\n",
       "      <td>-0.480000</td>\n",
       "      <td>-0.910100</td>\n",
       "      <td>944655.720000</td>\n",
       "      <td>4939402.091000</td>\n",
       "      <td>-0.009101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20211013</td>\n",
       "      <td>52.100000</td>\n",
       "      <td>52.190000</td>\n",
       "      <td>50.900000</td>\n",
       "      <td>51.750000</td>\n",
       "      <td>52.260000</td>\n",
       "      <td>-0.510000</td>\n",
       "      <td>-0.975900</td>\n",
       "      <td>649889.160000</td>\n",
       "      <td>3345977.425000</td>\n",
       "      <td>-0.009759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20211014</td>\n",
       "      <td>51.700000</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>51.200000</td>\n",
       "      <td>51.410000</td>\n",
       "      <td>51.750000</td>\n",
       "      <td>-0.340000</td>\n",
       "      <td>-0.657000</td>\n",
       "      <td>427006.000000</td>\n",
       "      <td>2198216.042000</td>\n",
       "      <td>-0.006570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20211015</td>\n",
       "      <td>51.130000</td>\n",
       "      <td>51.580000</td>\n",
       "      <td>50.620000</td>\n",
       "      <td>50.880000</td>\n",
       "      <td>51.410000</td>\n",
       "      <td>-0.530000</td>\n",
       "      <td>-1.030900</td>\n",
       "      <td>733016.990000</td>\n",
       "      <td>3738306.563000</td>\n",
       "      <td>-0.010309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20211018</td>\n",
       "      <td>51.080000</td>\n",
       "      <td>51.240000</td>\n",
       "      <td>49.680000</td>\n",
       "      <td>49.860000</td>\n",
       "      <td>50.880000</td>\n",
       "      <td>-1.020000</td>\n",
       "      <td>-2.004700</td>\n",
       "      <td>771971.370000</td>\n",
       "      <td>3862682.042000</td>\n",
       "      <td>-0.020047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20211019</td>\n",
       "      <td>49.850000</td>\n",
       "      <td>51.850000</td>\n",
       "      <td>49.700000</td>\n",
       "      <td>51.450000</td>\n",
       "      <td>49.860000</td>\n",
       "      <td>1.590000</td>\n",
       "      <td>3.188900</td>\n",
       "      <td>847527.050000</td>\n",
       "      <td>4332898.990000</td>\n",
       "      <td>0.031889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20211020</td>\n",
       "      <td>51.700000</td>\n",
       "      <td>52.040000</td>\n",
       "      <td>50.790000</td>\n",
       "      <td>51.370000</td>\n",
       "      <td>51.450000</td>\n",
       "      <td>-0.080000</td>\n",
       "      <td>-0.155500</td>\n",
       "      <td>668238.960000</td>\n",
       "      <td>3429513.908000</td>\n",
       "      <td>-0.001555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20211021</td>\n",
       "      <td>51.550000</td>\n",
       "      <td>54.880000</td>\n",
       "      <td>51.510000</td>\n",
       "      <td>54.280000</td>\n",
       "      <td>51.370000</td>\n",
       "      <td>2.910000</td>\n",
       "      <td>5.664800</td>\n",
       "      <td>2110058.330000</td>\n",
       "      <td>11318517.616000</td>\n",
       "      <td>0.056648</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20211022</td>\n",
       "      <td>54.680000</td>\n",
       "      <td>54.850000</td>\n",
       "      <td>53.600000</td>\n",
       "      <td>54.290000</td>\n",
       "      <td>54.280000</td>\n",
       "      <td>0.010000</td>\n",
       "      <td>0.018400</td>\n",
       "      <td>1026330.320000</td>\n",
       "      <td>5559123.303000</td>\n",
       "      <td>0.000184</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       ts_code trade_date      open      high       low     close  pre_close  \\\n",
       "100  601318.SH   20210927 47.900000 49.240000 47.820000 49.000000  48.080000   \n",
       "99   601318.SH   20210928 48.990000 49.630000 48.520000 49.260000  49.000000   \n",
       "98   601318.SH   20210929 48.770000 49.540000 48.520000 49.190000  49.260000   \n",
       "97   601318.SH   20210930 49.300000 49.300000 48.230000 48.360000  49.190000   \n",
       "96   601318.SH   20211008 50.500000 52.100000 50.110000 52.100000  48.360000   \n",
       "95   601318.SH   20211011 52.100000 53.390000 51.940000 52.740000  52.100000   \n",
       "94   601318.SH   20211012 52.050000 53.040000 51.680000 52.260000  52.740000   \n",
       "93   601318.SH   20211013 52.100000 52.190000 50.900000 51.750000  52.260000   \n",
       "92   601318.SH   20211014 51.700000 52.000000 51.200000 51.410000  51.750000   \n",
       "91   601318.SH   20211015 51.130000 51.580000 50.620000 50.880000  51.410000   \n",
       "90   601318.SH   20211018 51.080000 51.240000 49.680000 49.860000  50.880000   \n",
       "89   601318.SH   20211019 49.850000 51.850000 49.700000 51.450000  49.860000   \n",
       "88   601318.SH   20211020 51.700000 52.040000 50.790000 51.370000  51.450000   \n",
       "87   601318.SH   20211021 51.550000 54.880000 51.510000 54.280000  51.370000   \n",
       "86   601318.SH   20211022 54.680000 54.850000 53.600000 54.290000  54.280000   \n",
       "\n",
       "       change   pct_chg            vol          amount  netChangeRatio  \n",
       "100  0.920000  1.913500  990080.990000  4812486.506000        0.019135  \n",
       "99   0.260000  0.530600  779506.960000  3832059.452000        0.005306  \n",
       "98  -0.070000 -0.142100  631295.330000  3095105.433000       -0.001421  \n",
       "97  -0.830000 -1.687300  680070.250000  3300543.923000       -0.016873  \n",
       "96   3.740000  7.733700 2180028.230000 11199501.310000        0.077337  \n",
       "95   0.640000  1.228400 1504499.540000  7944560.509000        0.012284  \n",
       "94  -0.480000 -0.910100  944655.720000  4939402.091000       -0.009101  \n",
       "93  -0.510000 -0.975900  649889.160000  3345977.425000       -0.009759  \n",
       "92  -0.340000 -0.657000  427006.000000  2198216.042000       -0.006570  \n",
       "91  -0.530000 -1.030900  733016.990000  3738306.563000       -0.010309  \n",
       "90  -1.020000 -2.004700  771971.370000  3862682.042000       -0.020047  \n",
       "89   1.590000  3.188900  847527.050000  4332898.990000        0.031889  \n",
       "88  -0.080000 -0.155500  668238.960000  3429513.908000       -0.001555  \n",
       "87   2.910000  5.664800 2110058.330000 11318517.616000        0.056648  \n",
       "86   0.010000  0.018400 1026330.320000  5559123.303000        0.000184  "
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zgpa_df[60:75]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "3ea1ee85",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>change</th>\n",
       "      <th>pct_chg</th>\n",
       "      <th>vol</th>\n",
       "      <th>amount</th>\n",
       "      <th>netChangeRatio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20210726</td>\n",
       "      <td>57.090000</td>\n",
       "      <td>57.090000</td>\n",
       "      <td>54.330000</td>\n",
       "      <td>54.500000</td>\n",
       "      <td>57.640000</td>\n",
       "      <td>-3.140000</td>\n",
       "      <td>-5.447600</td>\n",
       "      <td>1174864.670000</td>\n",
       "      <td>6496203.840000</td>\n",
       "      <td>-0.054476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20210819</td>\n",
       "      <td>55.590000</td>\n",
       "      <td>55.760000</td>\n",
       "      <td>53.660000</td>\n",
       "      <td>53.710000</td>\n",
       "      <td>56.040000</td>\n",
       "      <td>-2.330000</td>\n",
       "      <td>-4.157700</td>\n",
       "      <td>1148606.030000</td>\n",
       "      <td>6231137.142000</td>\n",
       "      <td>-0.041577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20210702</td>\n",
       "      <td>64.030000</td>\n",
       "      <td>64.070000</td>\n",
       "      <td>62.100000</td>\n",
       "      <td>62.300000</td>\n",
       "      <td>64.760000</td>\n",
       "      <td>-2.460000</td>\n",
       "      <td>-3.798600</td>\n",
       "      <td>1028081.620000</td>\n",
       "      <td>6464701.802000</td>\n",
       "      <td>-0.037986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20220125</td>\n",
       "      <td>52.600000</td>\n",
       "      <td>52.900000</td>\n",
       "      <td>51.100000</td>\n",
       "      <td>51.200000</td>\n",
       "      <td>53.130000</td>\n",
       "      <td>-1.930000</td>\n",
       "      <td>-3.632600</td>\n",
       "      <td>776662.100000</td>\n",
       "      <td>4032087.602000</td>\n",
       "      <td>-0.036326</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20211029</td>\n",
       "      <td>50.820000</td>\n",
       "      <td>51.230000</td>\n",
       "      <td>49.240000</td>\n",
       "      <td>49.570000</td>\n",
       "      <td>51.300000</td>\n",
       "      <td>-1.730000</td>\n",
       "      <td>-3.372300</td>\n",
       "      <td>1466626.600000</td>\n",
       "      <td>7317467.292000</td>\n",
       "      <td>-0.033723</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       ts_code trade_date      open      high       low     close  pre_close  \\\n",
       "143  601318.SH   20210726 57.090000 57.090000 54.330000 54.500000  57.640000   \n",
       "125  601318.SH   20210819 55.590000 55.760000 53.660000 53.710000  56.040000   \n",
       "159  601318.SH   20210702 64.030000 64.070000 62.100000 62.300000  64.760000   \n",
       "20   601318.SH   20220125 52.600000 52.900000 51.100000 51.200000  53.130000   \n",
       "81   601318.SH   20211029 50.820000 51.230000 49.240000 49.570000  51.300000   \n",
       "\n",
       "       change   pct_chg            vol         amount  netChangeRatio  \n",
       "143 -3.140000 -5.447600 1174864.670000 6496203.840000       -0.054476  \n",
       "125 -2.330000 -4.157700 1148606.030000 6231137.142000       -0.041577  \n",
       "159 -2.460000 -3.798600 1028081.620000 6464701.802000       -0.037986  \n",
       "20  -1.930000 -3.632600  776662.100000 4032087.602000       -0.036326  \n",
       "81  -1.730000 -3.372300 1466626.600000 7317467.292000       -0.033723  "
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# sort_index是针对索引列的\n",
    "zgpa_df.sort_values(by='netChangeRatio')[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "12aa0f79",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>change</th>\n",
       "      <th>pct_chg</th>\n",
       "      <th>vol</th>\n",
       "      <th>amount</th>\n",
       "      <th>netChangeRatio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20211008</td>\n",
       "      <td>50.500000</td>\n",
       "      <td>52.100000</td>\n",
       "      <td>50.110000</td>\n",
       "      <td>52.100000</td>\n",
       "      <td>48.360000</td>\n",
       "      <td>3.740000</td>\n",
       "      <td>7.733700</td>\n",
       "      <td>2180028.230000</td>\n",
       "      <td>11199501.310000</td>\n",
       "      <td>0.077337</td>\n",
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       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20211021</td>\n",
       "      <td>51.550000</td>\n",
       "      <td>54.880000</td>\n",
       "      <td>51.510000</td>\n",
       "      <td>54.280000</td>\n",
       "      <td>51.370000</td>\n",
       "      <td>2.910000</td>\n",
       "      <td>5.664800</td>\n",
       "      <td>2110058.330000</td>\n",
       "      <td>11318517.616000</td>\n",
       "      <td>0.056648</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20211111</td>\n",
       "      <td>49.110000</td>\n",
       "      <td>51.160000</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>51.150000</td>\n",
       "      <td>49.130000</td>\n",
       "      <td>2.020000</td>\n",
       "      <td>4.111500</td>\n",
       "      <td>1110858.450000</td>\n",
       "      <td>5599660.442000</td>\n",
       "      <td>0.041115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20220207</td>\n",
       "      <td>51.340000</td>\n",
       "      <td>52.470000</td>\n",
       "      <td>50.700000</td>\n",
       "      <td>51.980000</td>\n",
       "      <td>49.970000</td>\n",
       "      <td>2.010000</td>\n",
       "      <td>4.022400</td>\n",
       "      <td>940416.500000</td>\n",
       "      <td>4858781.710000</td>\n",
       "      <td>0.040224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20220120</td>\n",
       "      <td>51.500000</td>\n",
       "      <td>53.520000</td>\n",
       "      <td>51.450000</td>\n",
       "      <td>53.400000</td>\n",
       "      <td>51.450000</td>\n",
       "      <td>1.950000</td>\n",
       "      <td>3.790100</td>\n",
       "      <td>1448359.410000</td>\n",
       "      <td>7661793.651000</td>\n",
       "      <td>0.037901</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      ts_code trade_date      open      high       low     close  pre_close  \\\n",
       "96  601318.SH   20211008 50.500000 52.100000 50.110000 52.100000  48.360000   \n",
       "87  601318.SH   20211021 51.550000 54.880000 51.510000 54.280000  51.370000   \n",
       "72  601318.SH   20211111 49.110000 51.160000 49.000000 51.150000  49.130000   \n",
       "16  601318.SH   20220207 51.340000 52.470000 50.700000 51.980000  49.970000   \n",
       "23  601318.SH   20220120 51.500000 53.520000 51.450000 53.400000  51.450000   \n",
       "\n",
       "     change  pct_chg            vol          amount  netChangeRatio  \n",
       "96 3.740000 7.733700 2180028.230000 11199501.310000        0.077337  \n",
       "87 2.910000 5.664800 2110058.330000 11318517.616000        0.056648  \n",
       "72 2.020000 4.111500 1110858.450000  5599660.442000        0.041115  \n",
       "16 2.010000 4.022400  940416.500000  4858781.710000        0.040224  \n",
       "23 1.950000 3.790100 1448359.410000  7661793.651000        0.037901  "
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zgpa_df.sort_values(by='netChangeRatio', ascending=False)[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "791f117b",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(zgpa_df[['vol']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "bf512e3e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 161 entries, 160 to 0\n",
      "Data columns (total 12 columns):\n",
      " #   Column          Non-Null Count  Dtype  \n",
      "---  ------          --------------  -----  \n",
      " 0   ts_code         161 non-null    object \n",
      " 1   trade_date      161 non-null    object \n",
      " 2   open            161 non-null    float64\n",
      " 3   high            161 non-null    float64\n",
      " 4   low             161 non-null    float64\n",
      " 5   close           161 non-null    float64\n",
      " 6   pre_close       161 non-null    float64\n",
      " 7   change          161 non-null    float64\n",
      " 8   pct_chg         161 non-null    float64\n",
      " 9   vol             161 non-null    float64\n",
      " 10  amount          161 non-null    float64\n",
      " 11  netChangeRatio  161 non-null    float64\n",
      "dtypes: float64(10), object(2)\n",
      "memory usage: 20.4+ KB\n"
     ]
    }
   ],
   "source": [
    "zgpa_df.info()\n",
    "#zgpa_df[['vol']].apply(lambda x:format(float(x),','))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "6a1d939c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "  <tbody>\n",
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       "      <th>160</th>\n",
       "      <td>692617.350000</td>\n",
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       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>1028081.620000</td>\n",
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       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>750646.750000</td>\n",
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       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>685812.850000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>523167.540000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>463601.660000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>975396.020000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>544416.390000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>731883.260000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>568035.790000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>161 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               vol\n",
       "160  692617.350000\n",
       "159 1028081.620000\n",
       "158  750646.750000\n",
       "157  685812.850000\n",
       "156  523167.540000\n",
       "..             ...\n",
       "4    463601.660000\n",
       "3    975396.020000\n",
       "2    544416.390000\n",
       "1    731883.260000\n",
       "0    568035.790000\n",
       "\n",
       "[161 rows x 1 columns]"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.set_option('float_format', '{:f}'.format)\n",
    "zgpa_df[['vol']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "3d97cca2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "</style>\n",
       "<table id=\"T_bdde2\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >Model:</th>\n",
       "      <th id=\"T_bdde2_level0_col0\" class=\"col_heading level0 col0\" colspan=\"2\">Decision Tree</th>\n",
       "      <th id=\"T_bdde2_level0_col2\" class=\"col_heading level0 col2\" colspan=\"2\">Regression</th>\n",
       "      <th id=\"T_bdde2_level0_col4\" class=\"col_heading level0 col4\" colspan=\"2\">Random</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level1\" >Predicted:</th>\n",
       "      <th id=\"T_bdde2_level1_col0\" class=\"col_heading level1 col0\" >Tumour</th>\n",
       "      <th id=\"T_bdde2_level1_col1\" class=\"col_heading level1 col1\" >Non-Tumour</th>\n",
       "      <th id=\"T_bdde2_level1_col2\" class=\"col_heading level1 col2\" >Tumour</th>\n",
       "      <th id=\"T_bdde2_level1_col3\" class=\"col_heading level1 col3\" >Non-Tumour</th>\n",
       "      <th id=\"T_bdde2_level1_col4\" class=\"col_heading level1 col4\" >Tumour</th>\n",
       "      <th id=\"T_bdde2_level1_col5\" class=\"col_heading level1 col5\" >Non-Tumour</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >Actual Label:</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "      <th class=\"blank col5\" >&nbsp;</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_bdde2_level0_row0\" class=\"row_heading level0 row0\" >Tumour (Positive)</th>\n",
       "      <td id=\"T_bdde2_row0_col0\" class=\"data row0 col0\" >38.000000</td>\n",
       "      <td id=\"T_bdde2_row0_col1\" class=\"data row0 col1\" >2.000000</td>\n",
       "      <td id=\"T_bdde2_row0_col2\" class=\"data row0 col2\" >18.000000</td>\n",
       "      <td id=\"T_bdde2_row0_col3\" class=\"data row0 col3\" >22.000000</td>\n",
       "      <td id=\"T_bdde2_row0_col4\" class=\"data row0 col4\" >21</td>\n",
       "      <td id=\"T_bdde2_row0_col5\" class=\"data row0 col5\" >nan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_bdde2_level0_row1\" class=\"row_heading level0 row1\" >Non-Tumour (Negative)</th>\n",
       "      <td id=\"T_bdde2_row1_col0\" class=\"data row1 col0\" >19.000000</td>\n",
       "      <td id=\"T_bdde2_row1_col1\" class=\"data row1 col1\" >439.000000</td>\n",
       "      <td id=\"T_bdde2_row1_col2\" class=\"data row1 col2\" >6.000000</td>\n",
       "      <td id=\"T_bdde2_row1_col3\" class=\"data row1 col3\" >452.000000</td>\n",
       "      <td id=\"T_bdde2_row1_col4\" class=\"data row1 col4\" >226</td>\n",
       "      <td id=\"T_bdde2_row1_col5\" class=\"data row1 col5\" >232.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x288606760>"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib as mpl\n",
    "\n",
    "df = pd.DataFrame([[38.0, 2.0, 18.0, 22.0, 21, np.nan],[19, 439, 6, 452, 226,232]],\n",
    "                  index=pd.Index(['Tumour (Positive)', 'Non-Tumour (Negative)'], name='Actual Label:'),\n",
    "                  columns=pd.MultiIndex.from_product([['Decision Tree', 'Regression', 'Random'],['Tumour', 'Non-Tumour']], names=['Model:', 'Predicted:']))\n",
    "df.style"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "20636127",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>change</th>\n",
       "      <th>pct_chg</th>\n",
       "      <th>vol</th>\n",
       "      <th>amount</th>\n",
       "      <th>netChangeRatio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20210701</td>\n",
       "      <td>64.260000</td>\n",
       "      <td>65.170000</td>\n",
       "      <td>63.580000</td>\n",
       "      <td>64.760000</td>\n",
       "      <td>64.280000</td>\n",
       "      <td>0.480000</td>\n",
       "      <td>0.746700</td>\n",
       "      <td>692617.350000</td>\n",
       "      <td>4449223.158000</td>\n",
       "      <td>0.007467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20210702</td>\n",
       "      <td>64.030000</td>\n",
       "      <td>64.070000</td>\n",
       "      <td>62.100000</td>\n",
       "      <td>62.300000</td>\n",
       "      <td>64.760000</td>\n",
       "      <td>-2.460000</td>\n",
       "      <td>-3.798600</td>\n",
       "      <td>1028081.620000</td>\n",
       "      <td>6464701.802000</td>\n",
       "      <td>-0.037986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20210705</td>\n",
       "      <td>61.990000</td>\n",
       "      <td>62.280000</td>\n",
       "      <td>61.130000</td>\n",
       "      <td>61.910000</td>\n",
       "      <td>62.300000</td>\n",
       "      <td>-0.390000</td>\n",
       "      <td>-0.626000</td>\n",
       "      <td>750646.750000</td>\n",
       "      <td>4629283.875000</td>\n",
       "      <td>-0.006260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20210706</td>\n",
       "      <td>62.420000</td>\n",
       "      <td>63.140000</td>\n",
       "      <td>61.850000</td>\n",
       "      <td>62.900000</td>\n",
       "      <td>61.910000</td>\n",
       "      <td>0.990000</td>\n",
       "      <td>1.599100</td>\n",
       "      <td>685812.850000</td>\n",
       "      <td>4296674.949000</td>\n",
       "      <td>0.015991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20210707</td>\n",
       "      <td>62.690000</td>\n",
       "      <td>63.410000</td>\n",
       "      <td>62.090000</td>\n",
       "      <td>62.370000</td>\n",
       "      <td>62.900000</td>\n",
       "      <td>-0.530000</td>\n",
       "      <td>-0.842600</td>\n",
       "      <td>523167.540000</td>\n",
       "      <td>3272128.188000</td>\n",
       "      <td>-0.008426</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       ts_code trade_date      open      high       low     close  pre_close  \\\n",
       "160  601318.SH   20210701 64.260000 65.170000 63.580000 64.760000  64.280000   \n",
       "159  601318.SH   20210702 64.030000 64.070000 62.100000 62.300000  64.760000   \n",
       "158  601318.SH   20210705 61.990000 62.280000 61.130000 61.910000  62.300000   \n",
       "157  601318.SH   20210706 62.420000 63.140000 61.850000 62.900000  61.910000   \n",
       "156  601318.SH   20210707 62.690000 63.410000 62.090000 62.370000  62.900000   \n",
       "\n",
       "       change   pct_chg            vol         amount  netChangeRatio  \n",
       "160  0.480000  0.746700  692617.350000 4449223.158000        0.007467  \n",
       "159 -2.460000 -3.798600 1028081.620000 6464701.802000       -0.037986  \n",
       "158 -0.390000 -0.626000  750646.750000 4629283.875000       -0.006260  \n",
       "157  0.990000  1.599100  685812.850000 4296674.949000        0.015991  \n",
       "156 -0.530000 -0.842600  523167.540000 3272128.188000       -0.008426  "
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zgpa_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "d304af7d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Solarize_Light2', '_classic_test_patch', '_mpl-gallery', '_mpl-gallery-nogrid', 'bmh', 'classic', 'dark_background', 'fast', 'fivethirtyeight', 'ggplot', 'grayscale', 'seaborn-v0_8', 'seaborn-v0_8-bright', 'seaborn-v0_8-colorblind', 'seaborn-v0_8-dark', 'seaborn-v0_8-dark-palette', 'seaborn-v0_8-darkgrid', 'seaborn-v0_8-deep', 'seaborn-v0_8-muted', 'seaborn-v0_8-notebook', 'seaborn-v0_8-paper', 'seaborn-v0_8-pastel', 'seaborn-v0_8-poster', 'seaborn-v0_8-talk', 'seaborn-v0_8-ticks', 'seaborn-v0_8-white', 'seaborn-v0_8-whitegrid', 'tableau-colorblind10']\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    ">>> import numpy as np\n",
    ">>> import matplotlib.pyplot as plt\n",
    ">>> print(plt.style.available)\n",
    ">>> plt.style.use(['dark_background','seaborn-whitegrid','tableau-colorblind10'])\n",
    ">>> plt.plot(np.sin(np.linspace(0, 2 * np.pi)), 'r-o')\n",
    ">>>\n",
    ">>> # Some plotting code with the default style\n",
    ">>>\n",
    ">>> plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "55923ebe",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "160   64.760000\n",
       "159   62.300000\n",
       "158   61.910000\n",
       "Name: close, dtype: float64"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zgpa_df.close[:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "1929a9de",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "160         NaN\n",
       "159   -0.037986\n",
       "158   -0.006260\n",
       "Name: close, dtype: float64"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#pct_change需要注意序列排序问题\n",
    "zgpa_df.close.pct_change()[:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "96d7e2ad",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         NaN\n",
       "1   -0.012259\n",
       "2    0.012608\n",
       "Name: close, dtype: float64"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zgpa_df.close.sort_index(ascending=True).pct_change()[:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "4fc98743",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>change</th>\n",
       "      <th>pct_chg</th>\n",
       "      <th>vol</th>\n",
       "      <th>amount</th>\n",
       "      <th>netChangeRatio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20210701</td>\n",
       "      <td>64.260000</td>\n",
       "      <td>65.170000</td>\n",
       "      <td>63.580000</td>\n",
       "      <td>64.760000</td>\n",
       "      <td>64.280000</td>\n",
       "      <td>0.480000</td>\n",
       "      <td>0.746700</td>\n",
       "      <td>692617.350000</td>\n",
       "      <td>4449223.158000</td>\n",
       "      <td>0.007467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20210702</td>\n",
       "      <td>64.030000</td>\n",
       "      <td>64.070000</td>\n",
       "      <td>62.100000</td>\n",
       "      <td>62.300000</td>\n",
       "      <td>64.760000</td>\n",
       "      <td>-2.460000</td>\n",
       "      <td>-3.798600</td>\n",
       "      <td>1028081.620000</td>\n",
       "      <td>6464701.802000</td>\n",
       "      <td>-0.037986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20210705</td>\n",
       "      <td>61.990000</td>\n",
       "      <td>62.280000</td>\n",
       "      <td>61.130000</td>\n",
       "      <td>61.910000</td>\n",
       "      <td>62.300000</td>\n",
       "      <td>-0.390000</td>\n",
       "      <td>-0.626000</td>\n",
       "      <td>750646.750000</td>\n",
       "      <td>4629283.875000</td>\n",
       "      <td>-0.006260</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       ts_code trade_date      open      high       low     close  pre_close  \\\n",
       "160  601318.SH   20210701 64.260000 65.170000 63.580000 64.760000  64.280000   \n",
       "159  601318.SH   20210702 64.030000 64.070000 62.100000 62.300000  64.760000   \n",
       "158  601318.SH   20210705 61.990000 62.280000 61.130000 61.910000  62.300000   \n",
       "\n",
       "       change   pct_chg            vol         amount  netChangeRatio  \n",
       "160  0.480000  0.746700  692617.350000 4449223.158000        0.007467  \n",
       "159 -2.460000 -3.798600 1028081.620000 6464701.802000       -0.037986  \n",
       "158 -0.390000 -0.626000  750646.750000 4629283.875000       -0.006260  "
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zgpa_df[:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "21cfdd17",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#zgpa_df.close.pct_change(freq=\"5D\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "1a5350da",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>change</th>\n",
       "      <th>pct_chg</th>\n",
       "      <th>vol</th>\n",
       "      <th>amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20220301</td>\n",
       "      <td>51.010000</td>\n",
       "      <td>51.400000</td>\n",
       "      <td>50.570000</td>\n",
       "      <td>51.390000</td>\n",
       "      <td>50.760000</td>\n",
       "      <td>0.630000</td>\n",
       "      <td>1.241100</td>\n",
       "      <td>568035.790000</td>\n",
       "      <td>2895181.121000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20220228</td>\n",
       "      <td>51.100000</td>\n",
       "      <td>51.100000</td>\n",
       "      <td>50.250000</td>\n",
       "      <td>50.760000</td>\n",
       "      <td>51.400000</td>\n",
       "      <td>-0.640000</td>\n",
       "      <td>-1.245100</td>\n",
       "      <td>731883.260000</td>\n",
       "      <td>3707888.597000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20220225</td>\n",
       "      <td>51.700000</td>\n",
       "      <td>52.060000</td>\n",
       "      <td>51.210000</td>\n",
       "      <td>51.400000</td>\n",
       "      <td>51.460000</td>\n",
       "      <td>-0.060000</td>\n",
       "      <td>-0.116600</td>\n",
       "      <td>544416.390000</td>\n",
       "      <td>2808109.116000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20220224</td>\n",
       "      <td>52.150000</td>\n",
       "      <td>52.250000</td>\n",
       "      <td>51.090000</td>\n",
       "      <td>51.460000</td>\n",
       "      <td>52.890000</td>\n",
       "      <td>-1.430000</td>\n",
       "      <td>-2.703700</td>\n",
       "      <td>975396.020000</td>\n",
       "      <td>5039207.433000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20220223</td>\n",
       "      <td>53.100000</td>\n",
       "      <td>53.300000</td>\n",
       "      <td>52.690000</td>\n",
       "      <td>52.890000</td>\n",
       "      <td>53.070000</td>\n",
       "      <td>-0.180000</td>\n",
       "      <td>-0.339200</td>\n",
       "      <td>463601.660000</td>\n",
       "      <td>2449763.789000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     ts_code  trade_date      open      high       low     close  pre_close  \\\n",
       "0  601318.SH    20220301 51.010000 51.400000 50.570000 51.390000  50.760000   \n",
       "1  601318.SH    20220228 51.100000 51.100000 50.250000 50.760000  51.400000   \n",
       "2  601318.SH    20220225 51.700000 52.060000 51.210000 51.400000  51.460000   \n",
       "3  601318.SH    20220224 52.150000 52.250000 51.090000 51.460000  52.890000   \n",
       "4  601318.SH    20220223 53.100000 53.300000 52.690000 52.890000  53.070000   \n",
       "\n",
       "     change   pct_chg           vol         amount  \n",
       "0  0.630000  1.241100 568035.790000 2895181.121000  \n",
       "1 -0.640000 -1.245100 731883.260000 3707888.597000  \n",
       "2 -0.060000 -0.116600 544416.390000 2808109.116000  \n",
       "3 -1.430000 -2.703700 975396.020000 5039207.433000  \n",
       "4 -0.180000 -0.339200 463601.660000 2449763.789000  "
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#zgpa_df.to_csv('./data/zhpa_df.csv', columns=zgpa_df.columns,index=True)\n",
    "zgpa_df_load=pd.read_csv('./data/zhpa_df.csv', parse_dates=True,index_col=0)\n",
    "zgpa_df=pd.read_csv('./data/zhpa_df.csv', parse_dates=True,index_col=0)\n",
    "\n",
    "# pct_chg is netChangeRatio，命名差异而已\n",
    "zgpa_df['netChangeRatio']=np.true_divide(zgpa_df['change'], zgpa_df['pre_close'])\n",
    "zgpa_df_load.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "307f5f0c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "zgpa_df.netChangeRatio.hist(bins=120)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "1f2c845f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.001, 0.00155]     17\n",
       "(0.00155, 0.00327]    16\n",
       "(0.00327, 0.00569]    16\n",
       "(0.00569, 0.00747]    16\n",
       "(0.00747, 0.00978]    16\n",
       "(0.00978, 0.0115]     16\n",
       "(0.0115, 0.015]       16\n",
       "(0.015, 0.02]         16\n",
       "(0.02, 0.0319]        16\n",
       "(0.0319, 0.0773]      16\n",
       "Name: netChangeRatio, dtype: int64"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cats=pd.qcut(np.abs(zgpa_df.netChangeRatio),10)\n",
    "cats.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "70750edb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.01, 0.0]      51\n",
       "(0.0, 0.01]       32\n",
       "(-0.02, -0.01]    27\n",
       "(0.01, 0.02]      18\n",
       "(-0.03, -0.02]    10\n",
       "(0.03, 0.04]       7\n",
       "(-0.04, -0.03]     5\n",
       "(0.02, 0.03]       5\n",
       "(0.04, 0.05]       2\n",
       "(0.05, 0.06]       1\n",
       "(0.07, 0.08]       1\n",
       "(-0.06, -0.05]     1\n",
       "(-0.05, -0.04]     1\n",
       "(0.08, 0.09]       0\n",
       "(0.06, 0.07]       0\n",
       "(-0.1, -0.09]      0\n",
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       "(-0.07, -0.06]     0\n",
       "(-0.08, -0.07]     0\n",
       "(0.09, 0.1]        0\n",
       "Name: netChangeRatio, dtype: int64"
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     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "bins=[ (float(x)-10)/100 for x in range(0,21)]\n",
    "#print(bins)\n",
    "cats=pd.cut(zgpa_df.netChangeRatio, bins)\n",
    "cats.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "25c87d50",
   "metadata": {
    "tags": []
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       "     cr_dummies_(-0.1, -0.09]  cr_dummies_(-0.09, -0.08]  \\\n",
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       "0                            0                          0   \n",
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       "[161 rows x 20 columns]"
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     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "change_ration_dummies=pd.get_dummies(cats, prefix='cr_dummies')\n",
    "change_ration_dummies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "9dbb8ec7",
   "metadata": {
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       "      <td>51.210000</td>\n",
       "      <td>51.400000</td>\n",
       "      <td>51.460000</td>\n",
       "      <td>-0.060000</td>\n",
       "      <td>-0.116600</td>\n",
       "      <td>544416.390000</td>\n",
       "      <td>2808109.116000</td>\n",
       "      <td>-0.001166</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20220224</td>\n",
       "      <td>52.150000</td>\n",
       "      <td>52.250000</td>\n",
       "      <td>51.090000</td>\n",
       "      <td>51.460000</td>\n",
       "      <td>52.890000</td>\n",
       "      <td>-1.430000</td>\n",
       "      <td>-2.703700</td>\n",
       "      <td>975396.020000</td>\n",
       "      <td>5039207.433000</td>\n",
       "      <td>-0.027037</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20220223</td>\n",
       "      <td>53.100000</td>\n",
       "      <td>53.300000</td>\n",
       "      <td>52.690000</td>\n",
       "      <td>52.890000</td>\n",
       "      <td>53.070000</td>\n",
       "      <td>-0.180000</td>\n",
       "      <td>-0.339200</td>\n",
       "      <td>463601.660000</td>\n",
       "      <td>2449763.789000</td>\n",
       "      <td>-0.003392</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     ts_code  trade_date      open      high       low     close  pre_close  \\\n",
       "0  601318.SH    20220301 51.010000 51.400000 50.570000 51.390000  50.760000   \n",
       "1  601318.SH    20220228 51.100000 51.100000 50.250000 50.760000  51.400000   \n",
       "2  601318.SH    20220225 51.700000 52.060000 51.210000 51.400000  51.460000   \n",
       "3  601318.SH    20220224 52.150000 52.250000 51.090000 51.460000  52.890000   \n",
       "4  601318.SH    20220223 53.100000 53.300000 52.690000 52.890000  53.070000   \n",
       "\n",
       "     change   pct_chg           vol         amount  netChangeRatio  positive  \n",
       "0  0.630000  1.241100 568035.790000 2895181.121000        0.012411         1  \n",
       "1 -0.640000 -1.245100 731883.260000 3707888.597000       -0.012451         0  \n",
       "2 -0.060000 -0.116600 544416.390000 2808109.116000       -0.001166         0  \n",
       "3 -1.430000 -2.703700 975396.020000 5039207.433000       -0.027037         0  \n",
       "4 -0.180000 -0.339200 463601.660000 2449763.789000       -0.003392         0  "
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zgpa_df['positive']=np.where(zgpa_df.netChangeRatio>0,1,0)\n",
    "zgpa_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "91f1a78f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>date_week</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022-03-01</td>\n",
       "      <td>20220301</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022-02-28</td>\n",
       "      <td>20220228</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022-02-25</td>\n",
       "      <td>20220225</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-02-24</td>\n",
       "      <td>20220224</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022-02-23</td>\n",
       "      <td>20220223</td>\n",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>2021-07-07</td>\n",
       "      <td>20210707</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>2021-07-06</td>\n",
       "      <td>20210706</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>2021-07-05</td>\n",
       "      <td>20210705</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>2021-07-02</td>\n",
       "      <td>20210702</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>2021-07-01</td>\n",
       "      <td>20210701</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>161 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          date  trade_date  date_week\n",
       "0   2022-03-01    20220301          1\n",
       "1   2022-02-28    20220228          0\n",
       "2   2022-02-25    20220225          4\n",
       "3   2022-02-24    20220224          3\n",
       "4   2022-02-23    20220223          2\n",
       "..         ...         ...        ...\n",
       "156 2021-07-07    20210707          2\n",
       "157 2021-07-06    20210706          1\n",
       "158 2021-07-05    20210705          0\n",
       "159 2021-07-02    20210702          4\n",
       "160 2021-07-01    20210701          3\n",
       "\n",
       "[161 rows x 3 columns]"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zgpa_df['date'] = zgpa_df['trade_date'].apply(lambda x: pd.to_datetime(str(x), format='%Y%m%d'))\n",
    "\n",
    "zgpa_df['date_week']=zgpa_df[\"date\"].dt.weekday\n",
    "zgpa_df[['date','trade_date','date_week']]\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "0222639c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <td>17</td>\n",
       "      <td>16</td>\n",
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       "      <th>4</th>\n",
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       "      <td>13</td>\n",
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       "</table>\n",
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      ],
      "text/plain": [
       "positive    0   1\n",
       "date_week        \n",
       "0          20  11\n",
       "1          18  14\n",
       "2          20  12\n",
       "3          17  16\n",
       "4          20  13"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xt=pd.crosstab(zgpa_df.date_week, zgpa_df.positive)\n",
    "xt\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "4a5cf180",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "      <th>2</th>\n",
       "      <td>0.625000</td>\n",
       "      <td>0.375000</td>\n",
       "    </tr>\n",
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       "      <th>3</th>\n",
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       "      <td>0.484848</td>\n",
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      ],
      "text/plain": [
       "positive         0        1\n",
       "date_week                  \n",
       "0         0.645161 0.354839\n",
       "1         0.562500 0.437500\n",
       "2         0.625000 0.375000\n",
       "3         0.515152 0.484848\n",
       "4         0.606061 0.393939"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xt_pct=xt.div(xt.sum(1).astype(float), axis=0)\n",
    "xt_pct"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "e16836aa",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'positive')"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xt_pct.plot(figsize=(8,5), kind='bar', stacked=True, title='date_week -> positive')\n",
    "plt.xlabel('date_week')\n",
    "plt.ylabel('positive')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "829f979e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Int64Index([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,\n",
       "            ...\n",
       "            151, 152, 153, 154, 155, 156, 157, 158, 159, 160],\n",
       "           dtype='int64', length=161)"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#zgpa_df.pivot_table(['positive', columns=['date_week']])\n",
    "#groupby\n",
    "zgpa_df.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "f6965388",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "date_week  positive\n",
       "0          0           20\n",
       "           1           11\n",
       "1          0           18\n",
       "           1           14\n",
       "2          0           20\n",
       "           1           12\n",
       "3          0           17\n",
       "           1           16\n",
       "4          0           20\n",
       "           1           13\n",
       "Name: positive, dtype: int64"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zgpa_df.groupby(['date_week','positive'])['positive'].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "eab2a3d5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>positive</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date_week</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.354839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.437500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.375000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.484848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.393939</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           positive\n",
       "date_week          \n",
       "0          0.354839\n",
       "1          0.437500\n",
       "2          0.375000\n",
       "3          0.484848\n",
       "4          0.393939"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zgpa_df.set_index('date_week',append=True)\n",
    "zgpa_df.pivot_table(['positive'],index=['date_week'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "ff0284be",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.489155\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 161 entries, 0 to 160\n",
      "Data columns (total 15 columns):\n",
      " #   Column          Non-Null Count  Dtype         \n",
      "---  ------          --------------  -----         \n",
      " 0   ts_code         161 non-null    object        \n",
      " 1   trade_date      161 non-null    int64         \n",
      " 2   open            161 non-null    float64       \n",
      " 3   high            161 non-null    float64       \n",
      " 4   low             161 non-null    float64       \n",
      " 5   close           161 non-null    float64       \n",
      " 6   pre_close       161 non-null    float64       \n",
      " 7   change          161 non-null    float64       \n",
      " 8   pct_chg         161 non-null    float64       \n",
      " 9   vol             161 non-null    float64       \n",
      " 10  amount          161 non-null    float64       \n",
      " 11  netChangeRatio  161 non-null    float64       \n",
      " 12  positive        161 non-null    int64         \n",
      " 13  date            161 non-null    datetime64[ns]\n",
      " 14  date_week       161 non-null    int64         \n",
      "dtypes: datetime64[ns](1), float64(10), int64(3), object(1)\n",
      "memory usage: 20.1+ KB\n"
     ]
    }
   ],
   "source": [
    "jump_threshold=zgpa_df.close.median()*0.0095\n",
    "print(jump_threshold)\n",
    "zgpa_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "46ae56b5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>jump</th>\n",
       "      <th>jump_power</th>\n",
       "      <th>close</th>\n",
       "      <th>date</th>\n",
       "      <th>netChangeRatio</th>\n",
       "      <th>pre_close</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-1</td>\n",
       "      <td>1.308379</td>\n",
       "      <td>51.460000</td>\n",
       "      <td>2022-02-24</td>\n",
       "      <td>-0.027037</td>\n",
       "      <td>52.890000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>-1</td>\n",
       "      <td>1.144831</td>\n",
       "      <td>53.070000</td>\n",
       "      <td>2022-02-22</td>\n",
       "      <td>-0.020126</td>\n",
       "      <td>54.160000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1</td>\n",
       "      <td>1.492369</td>\n",
       "      <td>51.980000</td>\n",
       "      <td>2022-02-07</td>\n",
       "      <td>0.040224</td>\n",
       "      <td>49.970000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>1</td>\n",
       "      <td>3.577598</td>\n",
       "      <td>52.100000</td>\n",
       "      <td>2021-10-08</td>\n",
       "      <td>0.077337</td>\n",
       "      <td>48.360000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>-1</td>\n",
       "      <td>1.226605</td>\n",
       "      <td>47.780000</td>\n",
       "      <td>2021-09-22</td>\n",
       "      <td>-0.018488</td>\n",
       "      <td>48.680000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>1</td>\n",
       "      <td>1.512813</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>2021-08-27</td>\n",
       "      <td>0.033797</td>\n",
       "      <td>50.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>-1</td>\n",
       "      <td>1.124388</td>\n",
       "      <td>54.500000</td>\n",
       "      <td>2021-07-26</td>\n",
       "      <td>-0.054476</td>\n",
       "      <td>57.640000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>-1</td>\n",
       "      <td>1.410596</td>\n",
       "      <td>62.300000</td>\n",
       "      <td>2021-07-02</td>\n",
       "      <td>-0.037986</td>\n",
       "      <td>64.760000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     jump  jump_power     close       date  netChangeRatio  pre_close\n",
       "3      -1    1.308379 51.460000 2022-02-24       -0.027037  52.890000\n",
       "5      -1    1.144831 53.070000 2022-02-22       -0.020126  54.160000\n",
       "16      1    1.492369 51.980000 2022-02-07        0.040224  49.970000\n",
       "96      1    3.577598 52.100000 2021-10-08        0.077337  48.360000\n",
       "103    -1    1.226605 47.780000 2021-09-22       -0.018488  48.680000\n",
       "119     1    1.512813 52.000000 2021-08-27        0.033797  50.300000\n",
       "143    -1    1.124388 54.500000 2021-07-26       -0.054476  57.640000\n",
       "159    -1    1.410596 62.300000 2021-07-02       -0.037986  64.760000"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jump_pd=pd.DataFrame()\n",
    "def judge_jump(today):\n",
    "    global jump_pd\n",
    "    if today.netChangeRatio>0 and (today.low-today.pre_close)>jump_threshold:\n",
    "        \"\"\"\n",
    "        符合向上跳空\n",
    "        \"\"\"\n",
    "        today['jump']=1\n",
    "        today['jump_power']=(today.low-today.pre_close)/jump_threshold\n",
    "        jump_pd=jump_pd.append(today)\n",
    "    elif today.netChangeRatio<0 and (today.pre_close-today.high)>jump_threshold:\n",
    "        \"\"\"\n",
    "        符合向下跳空\n",
    "        \"\"\"\n",
    "        today['jump']=-1\n",
    "        today['jump_power']=(today.pre_close-today.high)/jump_threshold\n",
    "        jump_pd=jump_pd.append(today)\n",
    "for kl_index in np.arange(0, zgpa_df.shape[0]):\n",
    "    today=zgpa_df.iloc[kl_index]\n",
    "    #print(today)\n",
    "    judge_jump(today)\n",
    "jump_pd.filter(['jump','jump_power','close','date', 'netChangeRatio','pre_close'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "b5e0c82d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      20220301\n",
       "1      20220228\n",
       "2      20220225\n",
       "3      20220224\n",
       "4      20220223\n",
       "         ...   \n",
       "156    20210707\n",
       "157    20210706\n",
       "158    20210705\n",
       "159    20210702\n",
       "160    20210701\n",
       "Name: trade_date, Length: 161, dtype: int64"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from canna import ABuMarketDrawing\n",
    "zgpa_df.set_index('date',append=True)\n",
    "jump_pd.index\n",
    "\n",
    "pd.to_numeric( zgpa_df['trade_date'], errors='coerce').fillna('0').astype('int64')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "317f3be7",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 161 entries, 0 to 160\n",
      "Data columns (total 15 columns):\n",
      " #   Column          Non-Null Count  Dtype         \n",
      "---  ------          --------------  -----         \n",
      " 0   ts_code         161 non-null    object        \n",
      " 1   trade_date      161 non-null    int64         \n",
      " 2   open            161 non-null    float64       \n",
      " 3   high            161 non-null    float64       \n",
      " 4   low             161 non-null    float64       \n",
      " 5   close           161 non-null    float64       \n",
      " 6   pre_close       161 non-null    float64       \n",
      " 7   change          161 non-null    float64       \n",
      " 8   pct_chg         161 non-null    float64       \n",
      " 9   vol             161 non-null    float64       \n",
      " 10  amount          161 non-null    float64       \n",
      " 11  netChangeRatio  161 non-null    float64       \n",
      " 12  positive        161 non-null    int64         \n",
      " 13  date            161 non-null    datetime64[ns]\n",
      " 14  date_week       161 non-null    int64         \n",
      "dtypes: datetime64[ns](1), float64(10), int64(3), object(1)\n",
      "memory usage: 20.1+ KB\n"
     ]
    }
   ],
   "source": [
    "zgpa_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "647c4007",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>change</th>\n",
       "      <th>pct_chg</th>\n",
       "      <th>vol</th>\n",
       "      <th>amount</th>\n",
       "      <th>netChangeRatio</th>\n",
       "      <th>positive</th>\n",
       "      <th>date</th>\n",
       "      <th>date_week</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-03-01</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20220301</td>\n",
       "      <td>51.010000</td>\n",
       "      <td>51.400000</td>\n",
       "      <td>50.570000</td>\n",
       "      <td>51.390000</td>\n",
       "      <td>50.760000</td>\n",
       "      <td>0.630000</td>\n",
       "      <td>1.241100</td>\n",
       "      <td>568035.790000</td>\n",
       "      <td>2895181.121000</td>\n",
       "      <td>0.012411</td>\n",
       "      <td>1</td>\n",
       "      <td>2022-03-01</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-28</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20220228</td>\n",
       "      <td>51.100000</td>\n",
       "      <td>51.100000</td>\n",
       "      <td>50.250000</td>\n",
       "      <td>50.760000</td>\n",
       "      <td>51.400000</td>\n",
       "      <td>-0.640000</td>\n",
       "      <td>-1.245100</td>\n",
       "      <td>731883.260000</td>\n",
       "      <td>3707888.597000</td>\n",
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       "      <td>2022-02-28</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-25</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20220225</td>\n",
       "      <td>51.700000</td>\n",
       "      <td>52.060000</td>\n",
       "      <td>51.210000</td>\n",
       "      <td>51.400000</td>\n",
       "      <td>51.460000</td>\n",
       "      <td>-0.060000</td>\n",
       "      <td>-0.116600</td>\n",
       "      <td>544416.390000</td>\n",
       "      <td>2808109.116000</td>\n",
       "      <td>-0.001166</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-02-25</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-24</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20220224</td>\n",
       "      <td>52.150000</td>\n",
       "      <td>52.250000</td>\n",
       "      <td>51.090000</td>\n",
       "      <td>51.460000</td>\n",
       "      <td>52.890000</td>\n",
       "      <td>-1.430000</td>\n",
       "      <td>-2.703700</td>\n",
       "      <td>975396.020000</td>\n",
       "      <td>5039207.433000</td>\n",
       "      <td>-0.027037</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-02-24</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-23</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20220223</td>\n",
       "      <td>53.100000</td>\n",
       "      <td>53.300000</td>\n",
       "      <td>52.690000</td>\n",
       "      <td>52.890000</td>\n",
       "      <td>53.070000</td>\n",
       "      <td>-0.180000</td>\n",
       "      <td>-0.339200</td>\n",
       "      <td>463601.660000</td>\n",
       "      <td>2449763.789000</td>\n",
       "      <td>-0.003392</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-02-23</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-07</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20210707</td>\n",
       "      <td>62.690000</td>\n",
       "      <td>63.410000</td>\n",
       "      <td>62.090000</td>\n",
       "      <td>62.370000</td>\n",
       "      <td>62.900000</td>\n",
       "      <td>-0.530000</td>\n",
       "      <td>-0.842600</td>\n",
       "      <td>523167.540000</td>\n",
       "      <td>3272128.188000</td>\n",
       "      <td>-0.008426</td>\n",
       "      <td>0</td>\n",
       "      <td>2021-07-07</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-06</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20210706</td>\n",
       "      <td>62.420000</td>\n",
       "      <td>63.140000</td>\n",
       "      <td>61.850000</td>\n",
       "      <td>62.900000</td>\n",
       "      <td>61.910000</td>\n",
       "      <td>0.990000</td>\n",
       "      <td>1.599100</td>\n",
       "      <td>685812.850000</td>\n",
       "      <td>4296674.949000</td>\n",
       "      <td>0.015991</td>\n",
       "      <td>1</td>\n",
       "      <td>2021-07-06</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-05</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20210705</td>\n",
       "      <td>61.990000</td>\n",
       "      <td>62.280000</td>\n",
       "      <td>61.130000</td>\n",
       "      <td>61.910000</td>\n",
       "      <td>62.300000</td>\n",
       "      <td>-0.390000</td>\n",
       "      <td>-0.626000</td>\n",
       "      <td>750646.750000</td>\n",
       "      <td>4629283.875000</td>\n",
       "      <td>-0.006260</td>\n",
       "      <td>0</td>\n",
       "      <td>2021-07-05</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-02</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20210702</td>\n",
       "      <td>64.030000</td>\n",
       "      <td>64.070000</td>\n",
       "      <td>62.100000</td>\n",
       "      <td>62.300000</td>\n",
       "      <td>64.760000</td>\n",
       "      <td>-2.460000</td>\n",
       "      <td>-3.798600</td>\n",
       "      <td>1028081.620000</td>\n",
       "      <td>6464701.802000</td>\n",
       "      <td>-0.037986</td>\n",
       "      <td>0</td>\n",
       "      <td>2021-07-02</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-01</th>\n",
       "      <td>601318.SH</td>\n",
       "      <td>20210701</td>\n",
       "      <td>64.260000</td>\n",
       "      <td>65.170000</td>\n",
       "      <td>63.580000</td>\n",
       "      <td>64.760000</td>\n",
       "      <td>64.280000</td>\n",
       "      <td>0.480000</td>\n",
       "      <td>0.746700</td>\n",
       "      <td>692617.350000</td>\n",
       "      <td>4449223.158000</td>\n",
       "      <td>0.007467</td>\n",
       "      <td>1</td>\n",
       "      <td>2021-07-01</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>161 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              ts_code  trade_date      open      high       low     close  \\\n",
       "date                                                                        \n",
       "2022-03-01  601318.SH    20220301 51.010000 51.400000 50.570000 51.390000   \n",
       "2022-02-28  601318.SH    20220228 51.100000 51.100000 50.250000 50.760000   \n",
       "2022-02-25  601318.SH    20220225 51.700000 52.060000 51.210000 51.400000   \n",
       "2022-02-24  601318.SH    20220224 52.150000 52.250000 51.090000 51.460000   \n",
       "2022-02-23  601318.SH    20220223 53.100000 53.300000 52.690000 52.890000   \n",
       "...               ...         ...       ...       ...       ...       ...   \n",
       "2021-07-07  601318.SH    20210707 62.690000 63.410000 62.090000 62.370000   \n",
       "2021-07-06  601318.SH    20210706 62.420000 63.140000 61.850000 62.900000   \n",
       "2021-07-05  601318.SH    20210705 61.990000 62.280000 61.130000 61.910000   \n",
       "2021-07-02  601318.SH    20210702 64.030000 64.070000 62.100000 62.300000   \n",
       "2021-07-01  601318.SH    20210701 64.260000 65.170000 63.580000 64.760000   \n",
       "\n",
       "            pre_close    change   pct_chg            vol         amount  \\\n",
       "date                                                                      \n",
       "2022-03-01  50.760000  0.630000  1.241100  568035.790000 2895181.121000   \n",
       "2022-02-28  51.400000 -0.640000 -1.245100  731883.260000 3707888.597000   \n",
       "2022-02-25  51.460000 -0.060000 -0.116600  544416.390000 2808109.116000   \n",
       "2022-02-24  52.890000 -1.430000 -2.703700  975396.020000 5039207.433000   \n",
       "2022-02-23  53.070000 -0.180000 -0.339200  463601.660000 2449763.789000   \n",
       "...               ...       ...       ...            ...            ...   \n",
       "2021-07-07  62.900000 -0.530000 -0.842600  523167.540000 3272128.188000   \n",
       "2021-07-06  61.910000  0.990000  1.599100  685812.850000 4296674.949000   \n",
       "2021-07-05  62.300000 -0.390000 -0.626000  750646.750000 4629283.875000   \n",
       "2021-07-02  64.760000 -2.460000 -3.798600 1028081.620000 6464701.802000   \n",
       "2021-07-01  64.280000  0.480000  0.746700  692617.350000 4449223.158000   \n",
       "\n",
       "            netChangeRatio  positive       date  date_week  \n",
       "date                                                        \n",
       "2022-03-01        0.012411         1 2022-03-01          1  \n",
       "2022-02-28       -0.012451         0 2022-02-28          0  \n",
       "2022-02-25       -0.001166         0 2022-02-25          4  \n",
       "2022-02-24       -0.027037         0 2022-02-24          3  \n",
       "2022-02-23       -0.003392         0 2022-02-23          2  \n",
       "...                    ...       ...        ...        ...  \n",
       "2021-07-07       -0.008426         0 2021-07-07          2  \n",
       "2021-07-06        0.015991         1 2021-07-06          1  \n",
       "2021-07-05       -0.006260         0 2021-07-05          0  \n",
       "2021-07-02       -0.037986         0 2021-07-02          4  \n",
       "2021-07-01        0.007467         1 2021-07-01          3  \n",
       "\n",
       "[161 rows x 15 columns]"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d=pd.to_numeric( zgpa_df['trade_date'], errors='coerce').fillna('0').astype('int64')\n",
    "d['date']=zgpa_df['date']\n",
    "\n",
    "\n",
    "zgpa_df.index=zgpa_df['date']\n",
    "zgpa_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "fdae8882",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 2000x1200 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#zgpa_df[['close']].values\n",
    "zgpa_df.index\n",
    "zgpa_df['volume']=zgpa_df['vol'].copy()\n",
    "zgpa_df.index.name=None\n",
    "zgpa_df['volume']=zgpa_df['volume'].astype(np.int64)\n",
    "zgpa_df.head()\n",
    "# Volume数值类型对应的应该是int64,不是float64\n",
    "ABuMarketDrawing.plot_candle_form_klpd(zgpa_df, view_indexs=jump_pd.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e53a476d-5502-4af1-8006-f3be92b0ddd5",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
